@article{kleyko2023efficient,
  title={Efficient decoding of compositional structure in holistic representations},
  author={Kleyko, Denis and Bybee, Connor and Huang, Ping-Chen and Kymn, Christopher J and Olshausen, Bruno A and Frady, E Paxon and Sommer, Friedrich T},
  journal={Neural Computation},
  pages={1--28},
  year={2023}
}

@article{KleykoSurveyVSA2023Part2,
author = {Kleyko, Denis and Rachkovskij, Dmitri and Osipov, Evgeny and Rahimi, Abbas},
title = {A Survey on Hyperdimensional Computing Aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges},
year = {2023},
issue_date = {September 2023},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {55},
number = {9},
issn = {0360-0300},
url = {https://doi.org/10.1145/3558000},
doi = {10.1145/3558000},
abstract = {This is Part II of the two-part comprehensive survey devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA). Both names refer to a family of computational models that use high-dimensional distributed representations and rely on the algebraic properties of their key operations to incorporate the advantages of structured symbolic representations and vector distributed representations. Holographic Reduced Representations is an influential HDC/VSA model that is well known in the machine learning domain and often used to refer to the whole family. However, for the sake of consistency, we use HDC/VSA to refer to the field.Part I of this survey covered foundational aspects of the field, such as the historical context leading to the development of HDC/VSA, key elements of any HDC/VSA model, known HDC/VSA models, and the transformation of input data of various types into high-dimensional vectors suitable for HDC/VSA. This second part surveys existing applications, the role of HDC/VSA in cognitive computing and architectures, as well as directions for future work. Most of the applications lie within the Machine Learning/Artificial Intelligence domain; however, we also cover other applications to provide a complete picture. The survey is written to be useful for both newcomers and practitioners.},
journal = {ACM Computing Surveys},
month = {jan},
articleno = {175},
numpages = {52},
keywords = {Vector Symbolic Architectures, Cognitive architectures, Hyperdimensional Computing, Tensor Product Representations, Distributed representations, Applications, Geometric Analogue of Holographic Reduced Representations, Modular Composite Representations, Holographic Reduced Representations, Binary Spatter Codes, Cognitive computing, Sparse Block Codes, Matrix Binding of Additive Terms, Sparse Binary Distributed Representations, Analogical reasoning, Artificial Intelligence, Multiply-Add-Permute, Machine learning}
}

@article{KleykoSurveyVSA2022Part1,
author = {Kleyko, Denis and Rachkovskij, Dmitri A. and Osipov, Evgeny and Rahimi, Abbas},
title = {A Survey on Hyperdimensional Computing Aka Vector Symbolic Architectures, Part I: Models and Data Transformations},
year = {2022},
issue_date = {June 2023},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {55},
number = {6},
issn = {0360-0300},
url = {https://doi.org/10.1145/3538531},
doi = {10.1145/3538531},
abstract = {This two-part comprehensive survey is devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA). Both names refer to a family of computational models that use high-dimensional distributed representations and rely on the algebraic properties of their key operations to incorporate the advantages of structured symbolic representations and distributed vector representations. Notable models in the HDC/VSA family are Tensor Product Representations, Holographic Reduced Representations, Multiply-Add-Permute, Binary Spatter Codes, and Sparse Binary Distributed Representations but there are other models too. HDC/VSA is a highly interdisciplinary field with connections to computer science, electrical engineering, artificial intelligence, mathematics, and cognitive science. This fact makes it challenging to create a thorough overview of the field. However, due to a surge of new researchers joining the field in recent years, the necessity for a comprehensive survey of the field has become extremely important. Therefore, amongst other aspects of the field, this Part I surveys important aspects such as: known computational models of HDC/VSA and transformations of various input data types to high-dimensional distributed representations. Part II of this survey is devoted to applications, cognitive computing and architectures, as well as directions for future work. The survey is written to be useful for both newcomers and practitioners.},
journal = {ACM Computing Surveys},
month = {dec},
articleno = {130},
numpages = {40},
keywords = {tensor product representations, matrix binding of additive terms, binary spatter codes, multiply-add-permute, artificial intelligence, distributed representations, sparse binary distributed representations, machine learning, modular composite representations, data structures, geometric analogue of holographic reduced representations, sparse block codes, hyperdimensional computing, vector symbolic architectures, holographic reduced representations}
}

@article{Sanborn_BNN,
doi = {10.48550/ARXIV.2209.03416},

url = {https://arxiv.org/abs/2209.03416},

author = {Sanborn, Sophia and Shewmake, Christian and Olshausen, Bruno and Hillar, Christopher},

keywords = {Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},

title = {Bispectral Neural Networks},

publisher = {arXiv},

year = {2022},

copyright = {Creative Commons Attribution Non Commercial No Derivatives 4.0 International}
}

@article{kleyko2022vector,
  title={Vector Symbolic Architectures as a Computing Framework for Emerging Hardware},
  author={Kleyko, Denis and Davies, Mike and Frady, Edward Paxon and Kanerva, Pentti and Kent, Spencer J and Olshausen, Bruno A and Osipov, Evgeny and Rabaey, Jan M and Rachkovskij, Dmitri A and Rahimi, Abbas and others},
  journal={Proceedings of the IEEE},
  volume={110},
  number={10},
  pages={1538--1571},
  year={2022},
  publisher={IEEE}
}

@article{dutell2022highfidelity,
author = {DuTell, Vasha and Gibaldi, Agostino and Focarelli, Giulia and Olshausen, Bruno A. and Banks, Marty S.},
title = {High-fidelity eye, head, body, and world tracking with a wearable device},
journal = {Behavior Research Methods},
year = {2022},
doi = {10.3758/s13428-022-01888-3}
}

@article{fang2022learning,
author = {Fang, Michael Y.-S. and Mudigonda, Mayur and Zarcone, Ryan and Khosrowshahi, Amir and Olshausen, Bruno A.},
title = “{Learning and Inference in Sparse Coding Models With Langevin Dynamics}”,
journal = {Neural Computation},
volume = {34},
number = {8},
pages = {1676-1700},
year = {2022},
month = {07},
issn = {0899-7667},
doi = {10.1162/neco_a_01505},
url = {https://doi.org/10.1162/neco\_a\_01505},
eprint = {https://direct.mit.edu/neco/article-pdf/34/8/1676/2034932/neco\_a\_01505.pdf},
}

@InProceedings{simon22reverse,
title = {Reverse Engineering the Neural Tangent Kernel},
author = {Simon, James Benjamin and Anand, Sajant and Deweese, Mike},
booktitle = {Proceedings of the 39th International Conference on Machine Learning},
pages = {20215–20231},
year = {2022},
editor = {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
volume = {162},
series = {Proceedings of Machine Learning Research},
month = {17–23 Jul},
publisher = {PMLR},
pdf = {https://proceedings.mlr.press/v162/simon22a/simon22a.pdf},
url = {https://proceedings.mlr.press/v162/simon22a.html},
abstract = {The development of methods to guide the design of neural networks is an important open challenge for deep learning theory. As a paradigm for principled neural architecture design, we propose the translation of high-performing kernels, which are better-understood and amenable to first-principles design, into equivalent network architectures, which have superior efficiency, flexibility, and feature learning. To this end, we constructively prove that, with just an appropriate choice of activation function, any positive-semidefinite dot-product kernel can be realized as either the NNGP or neural tangent kernel of a fully-connected neural network with only one hidden layer. We verify our construction numerically and demonstrate its utility as a design tool for finite fully-connected networks in several experiments.}
}

@misc{zhong2022limited,
doi = {10.48550/ARXIV.2205.08662},

url = {https://arxiv.org/abs/2205.08662},

author = {Zhong, Adrianne and DeWeese, Michael R.},

keywords = {Statistical Mechanics (cond-mat.stat-mech), FOS: Physical sciences, FOS: Physical sciences},

title = {Limited-control optimal protocols arbitrarily far from equilibrium},

publisher = {arXiv},

year = {2022},

copyright = {arXiv.org perpetual, non-exclusive license}
}

@article{frim2022geometric,
title = {Geometric Bound on the Efficiency of Irreversible Thermodynamic Cycles},
author = {Frim, Adam G. and DeWeese, Michael R.},
journal = {Phys. Rev. Lett.},
volume = {128},
issue = {23},
pages = {230601},
numpages = {7},
year = {2022},
month = {Jun},
publisher = {American Physical Society},
doi = {10.1103/PhysRevLett.128.230601},
url = {https://link.aps.org/doi/10.1103/PhysRevLett.128.230601}
}

@article{frim2022optimal,
title = {Optimal finite-time Brownian Carnot engine},
author = {Frim, Adam G. and DeWeese, Michael R.},
journal = {Phys. Rev. E},
volume = {105},
issue = {5},
pages = {L052103},
numpages = {7},
year = {2022},
month = {May},
publisher = {American Physical Society},
doi = {10.1103/PhysRevE.105.L052103},
url = {https://link.aps.org/doi/10.1103/PhysRevE.105.L052103}
}

@incollection{kanerva2022hdmss,
title={Hyperdimensional Computing: An algebra for computing with vectors},
author={Kanerva, P.},
booktitle={Advances in Semiconductor Technologies},
year={2022},
publisher={Wiley}
}

@article{kleyko2022generalized,
  title={Generalized Key-Value Memory to Flexibly Adjust Redundancy in Memory-Augmented Networks},
  author={Kleyko, Denis and Karunaratne, Geethan and Rabaey, Jan M and Sebastian, Abu and Rahimi, Abbas},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2022},
  publisher={IEEE}
}

@article{wadia2022solution,
title = {Solution to the Fokker-Planck equation for slowly driven Brownian motion: Emergent geometry and a formula for the corresponding thermodynamic metric},
author = {Wadia, Neha S. and Zarcone, Ryan V. and DeWeese, Michael R.},
journal = {Phys. Rev. E},
volume = {105},
issue = {3},
pages = {034130},
numpages = {12},
year = {2022},
month = {Mar},
publisher = {American Physical Society},
doi = {10.1103/PhysRevE.105.034130},
url = {https://link.aps.org/doi/10.1103/PhysRevE.105.034130}
}

@article{ligeralde2022sparse,
  title={Sparse coding models predict a spectral bias in the development of primary visual cortex (V1) receptive fields},
  author={Ligeralde, Andrew and DeWeese, Michael R},
  journal={bioRxiv},
  year={2022},
  publisher={Cold Spring Harbor Laboratory}
}

@article{li2022neural,
  author    = {Zengyi Li and
               Yubei Chen and
               Yann LeCun and
               Friedrich T. Sommer},
  title     = {Neural Manifold Clustering and Embedding},
  journal   = {CoRR},
  volume    = {abs/2201.10000},
  year      = {2022},
  url       = {https://arxiv.org/abs/2201.10000},
  eprinttype = {arXiv},
  eprint    = {2201.10000},
  timestamp = {Tue, 01 Feb 2022 14:59:01 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2201-10000.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@misc{evans2021stochastic,
doi = {10.48550/ARXIV.2111.09896},

url = {https://arxiv.org/abs/2111.09896},

author = {Evans, Ethan N. and Wang, Ziyi and Frim, Adam G. and DeWeese, Michael R. and Theodorou, Evangelos A.},

keywords = {Quantum Physics (quant-ph), Optimization and Control (math.OC), FOS: Physical sciences, FOS: Physical sciences, FOS: Mathematics, FOS: Mathematics},

title = {Stochastic optimization for learning quantum state feedback control},

publisher = {arXiv},

year = {2021},

copyright = {Creative Commons Attribution 4.0 International}
}

@article{kleyko2021cellular,
  title={Cellular automata can reduce memory requirements of collective-state computing},
  author={Kleyko, Denis and Frady, Edward Paxon and Sommer, Friedrich T},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2021},
  publisher={IEEE}
}

@misc{simon2021neural,
title={Neural Tangent Kernel Eigenvalues Accurately Predict Generalization},
author={James B. Simon and Madeline Dickens and Michael R. DeWeese},
year={2021},
eprint={2110.03922},
archivePrefix={arXiv},
primaryClass={cs.LG}
}

@article{frady2021variable,
  title={Variable binding for sparse distributed representations: theory and applications},
  author={Frady, Edward Paxon and Kleyko, Denis and Sommer, Friedrich T},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2021},
  publisher={IEEE}
}

@article{PhysRevE.104.014409,
title = {Choosing dynamical systems that predict weak input},
author = {Marzen, Sarah E.},
journal = {Phys. Rev. E},
volume = {104},
issue = {1},
pages = {014409},
numpages = {11},
year = {2021},
month = {Jul},
publisher = {American Physical Society},
doi = {10.1103/PhysRevE.104.014409},
url = {https://link.aps.org/doi/10.1103/PhysRevE.104.014409}
}

@inproceedings{yun-etal-2021-transformer,
    title = "Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors",
    author = "Yun, Zeyu  and
      Chen, Yubei  and
      Olshausen, Bruno  and
      LeCun, Yann",
    booktitle = "Proceedings of Deep Learning Inside Out (DeeLIO): The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.deelio-1.1",
    doi = "10.18653/v1/2021.deelio-1.1",
    pages = "1--10",
    abstract = "Transformer networks have revolutionized NLP representation learning since they were introduced. Though a great effort has been made to explain the representation in transformers, it is widely recognized that our understanding is not sufficient. One important reason is that there lack enough visualization tools for detailed analysis. In this paper, we propose to use dictionary learning to open up these {`}black boxes{'} as linear superpositions of transformer factors. Through visualization, we demonstrate the hierarchical semantic structures captured by the transformer factors, e.g., word-level polysemy disambiguation, sentence-level pattern formation, and long-range dependency. While some of these patterns confirm the conventional prior linguistic knowledge, the rest are relatively unexpected, which may provide new insights. We hope this visualization tool can bring further knowledge and a better understanding of how transformer networks work. The code is available at: https://github.com/zeyuyun1/TransformerVis.",
}

@article{frye2021critical,
author = {Frye, Charles G. and Simon, James and Wadia, Neha S. and Ligeralde, Andrew and DeWeese, Michael R. and Bouchard, Kristofer E.},
title = “{Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses}”,
journal = {Neural Computation},
volume = {33},
number = {6},
pages = {1469-1497},
year = {2021},
month = {05},
issn = {0899-7667},
doi = {10.1162/neco_a_01388},
url = {https://doi.org/10.1162/neco\_a\_01388},
eprint = {https://direct.mit.edu/neco/article-pdf/33/6/1469/1916370/neco\_a\_01388.pdf},
}

@article{frim2021engineered,
title = {Engineered swift equilibration for arbitrary geometries},
author = {Frim, Adam G. and Zhong, Adrianne and Chen, Shi-Fan and Mandal, Dibyendu and DeWeese, Michael R.},
journal = {Phys. Rev. E},
volume = {103},
issue = {3},
pages = {L030102},
numpages = {6},
year = {2021},
month = {Mar},
publisher = {American Physical Society},
doi = {10.1103/PhysRevE.103.L030102},
url = {https://link.aps.org/doi/10.1103/PhysRevE.103.L030102}
}

@article{li2021neural,
title={A Neural Network MCMC Sampler That Maximizes Proposal Entropy},
author={Li, Zengyi and Chen, Yubei and Sommer, Friedrich T},
journal={Entropy},
volume={23},
number={3},
pages={269},
year={2021},
publisher={Multidisciplinary Digital Publishing Institute}
}

@article{kleyko2020integer,
  title={Integer echo state networks: efficient reservoir computing for digital hardware},
  author={Kleyko, Denis and Frady, Edward Paxon and Kheffache, Mansour and Osipov, Evgeny},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2020},
  publisher={IEEE}
}

@misc{chau2020disentangling,
title={Disentangling images with Lie group transformations and sparse coding},
author={Ho Yin Chau and Frank Qiu and Yubei Chen and Bruno Olshausen},
year={2020},
eprint={2012.12071},
archivePrefix={arXiv},
primaryClass={cs.CV}
}

@article{frady2020resonator,
author = {Frady, E. Paxon and Kent, Spencer J. and Olshausen, Bruno A. and Sommer, Friedrich T.},
title = {Resonator networks, 1: an efficient solution for factoring high-dimensional, distributed representations of data structures},
journal = {Neural Computation},
volume = {32},
number = {12},
pages = {2311-2331},
year = {2020},
doi = {10.1162/neco\_a\_01331}
}

@article{kent2020resonator,
author = {Kent, Spencer J. and Frady, E. Paxon and Sommer, Friedrich T. and Olshausen, Bruno A.},
title = {Resonator networks, 2: factorization performance and capacity compared to optimization-based methods},
journal = {Neural Computation},
volume = {32},
number = {12},
pages = {2332-2388},
year = {2020},
doi = {10.1162/neco\_a\_01329}
}

@article{holman2020autonomous,
  title={Autonomous adaptive data acquisition for scanning hyperspectral imaging},
  author={Holman, Elizabeth A and Fang, Yuan-Sheng and Chen, Liang and DeWeese, Michael and Holman, Hoi-Ying N and Sternberg, Paul W},
  journal={Communications biology},
  volume={3},
  number={1},
  pages={1--7},
  year={2020},
  publisher={Nature Publishing Group}
}

@article{paiton2020selectivity,
author = {Paiton, Dylan M. and Frye, Charles G. and Lundquist, Sheng Y. and Bowen, Joel D. and Zarcone, Ryan and Olshausen, Bruno A.},
title = “{Selectivity and robustness of sparse coding networks}”,
journal = {Journal of Vision},
volume = {20},
number = {12},
pages = {1-28},
year = {2020},
doi = {10.1167/jov.20.12.10}
}

@misc{li2020neural,
title={A Neural Network MCMC sampler that maximizes Proposal Entropy},
author={Li, Zengyi and Chen, Yubei and Sommer, Friedrich T.},
year={2020},
eprint={2010.03587},
archivePrefix={arXiv},
primaryClass={stat.ML}
}

@article{hu2020rg,
title={RG-Flow: A hierarchical and explainable flow model based on renormalization group and sparse prior},
author={Hu, Hong-Ye and Wu, Dian and You, Yi-Zhuang and Olshausen, Bruno and Chen, Yubei},
journal={arXiv preprint arXiv:2010.00029},
year={2020}
}

@article{yerxa2020efficient,
  title={Efficient sensory coding of multidimensional stimuli},
  author={Yerxa, Thomas E and Kee, Eric and DeWeese, Michael R and Cooper, Emily A},
  journal={PLoS computational biology},
  volume={16},
  number={9},
  pages={e1008146},
  year={2020},
  publisher={Public Library of Science San Francisco, CA USA}
}

@Article{kleyko2020density,
title = {Density Encoding Enables Resource-Efficient Randomly Connected Neural Networks},
author = {Kleyko, Denis and Kheffache, Mansour and Frady, E. Paxon and Wiklund, Urban and Osipov, Evgeny},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
year = {2020},
volume = {},
number = {},
pages = {1–7}
}

@article{sachdeva2020heterogeneous,
title={Heterogeneous synaptic weighting improves neural coding in the presence of common noise},
author={Sachdeva, Pratik R. and Livezey, Jesse A. and DeWeese, Michael R.},
journal={Neural Computation},
volume={32},
number={7},
pages={1239–1276},
year={2020},
publisher={MIT Press}
}

@article{anderson2020high,
title={High-acuity vision from retinal image motion},
author={Anderson, Alexander G and Ratnam, Kavitha and Roorda, Austin and Olshausen, Bruno A},
journal={Journal of Vision},
volume={20},
number={7},
pages={34–34},
year={2020},
publisher={The Association for Research in Vision and Ophthalmology}
}

@article{frady2020resonatorpreprint,
title={Resonator networks for factoring distributed representations of data structures},
author={Frady, E. Paxon and Kent, Spencer J. and Olshausen, Bruno A. and Sommer, Friedrich T.},
journal={arXiv preprint, arXiv:2007.03748},
year={2020},
url={https://arxiv.org/abs/2007.03748}
}

@inproceedings{Wang20203DSR,
title={3D Shape Reconstruction from Free-Hand Sketches},
author={Wang and Jierui Lin and Qian Yu and Run-Tao Liu and Yubei Chen and Stella X. Yu},
year={2020}
}

@article{warner2020model,
title={A model for image segmentation in retina},
author={Christopher Warner and Friedrich T. Sommer},
journal={arXiv preprint, arXiv:2005.02567},
year={2020},
url={https://arxiv.org/abs/2005.02567}
}

@article{zarcone2020analog,
title={Analog coding in emerging Memory Systems},
author={Zarcone, Ryan V and Engel, Jesse H and Eryilmaz, S Burc and Wan, Weier and Kim, SangBum and BrightSky, Matthew and Lam, Chung and Lung, Hsiang-Lan and Olshausen, Bruno A and Wong, H-S Philip},
journal={Scientific Reports},
volume={10},
number={1},
pages={1–13},
year={2020},
publisher={Nature Publishing Group}
}

@inproceedings{wang2020orthogonal,
title={Orthogonal Convolutional Neural Networks},
author={Wang, Jiayun and Chen, Yubei and Chakraborty, Rudrasis and Yu, Stella X},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2020}
}

@article{sachdeva2020accurate,
title={Accurate inference in parametric models reshapes neuroscientific interpretation and improves data-driven discovery},
author={Sachdeva, Pratik S and Livezey, Jesse A and Dougherty, Maximilian E and Gu, Bon-Mi and Berke, Joshua D and Bouchard, Kristofer E},
journal={bioRxiv},
year={2020},
publisher={Cold Spring Harbor Laboratory}
}

@ARTICLE{frye2020critical,
author = {{Frye}, Charles G. and {Simon}, James and {Wadia}, Neha S. and {Ligeralde}, Andrew and {DeWeese}, Michael R. and
{Bouchard}, Kristofer E.},
title = “{Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses}”,
journal = {arXiv e-prints},
year = 2020,
month = Mar,
archivePrefix = {arXiv},
eprint = {2003.10397},
}

@inproceedings{paiton2020subspace,
title={Subspace locally competitive algorithms},
author={Paiton, Dylan M. and Shepard, Steven and Chan, Kwan Ho Ryan and Olshausen, Bruno A.},
booktitle={7th Annual Neuro-inspired Computational Elements Workshop},
year={2020},
location={Heidelberg, Germany},
organization={ACM}
}

@inproceedings{liu2019biologically,
title={Biologically Plausible Sequence Learning with Spiking Neural Networks},
author={Zuozhu Liu and Thiparat Chotibut and Christopher Hillar and Shaowei Lin},
year={2019},
eprint={1911.10943},
archivePrefix={arXiv},
primaryClass={cond-mat.dis-nn}
}

@article{barger2019robust,
title={Robust, automated sleep scoring by a compact neural network with distributional shift correction},
author={Barger, Zeke and Frye, Charles G and Liu, Danqian and Dan, Yang and Bouchard, Kristofer E},
journal={PloS one},
volume={14},
number={12},
pages={e0224642},
year={2019},
publisher={Public Library of Science San Francisco, CA USA}
}

@inproceedings{cheung2019superposition,
title = {Superposition of many models into one},
author = {Cheung, Brian and Terekhov, Alex and Chen, Yubei and Agrawal, Pulkit and Olshausen, Bruno},
booktitle = {Advances in Neural Information Processing Systems 32},
pages = {10867–10876},
url = {http://papers.nips.cc/paper/9269-superposition-of-many-models-into-one.pdf}
year = {2019}
}

@inproceedings{clark2019unsupervised,
title={Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis},
author={Clark, David and Livezey, Jesse and Bouchard, Kristofer},
booktitle={Advances in Neural Information Processing Systems},
pages={14267–14278},
year={2019}
}

@article{sachdeva2019pyuoi,
title={PyUoI: The Union of Intersections Framework in Python},
author={Sachdeva, Pratik and Livezey, Jesse and Tritt, Andrew and Bouchard, Kristofer},
journal={Journal of Open Source Software},
volume={4},
number={44},
pages={1799},
year={2019}
}

@article{garfinkle2019uniqueness,
title={On the uniqueness and stability of dictionaries for sparse representation of noisy signals},
author={Garfinkle, Charles J and Hillar, Christopher J},
journal={IEEE Transactions on Signal Processing},
volume={67},
number={23},
pages={5884–5892},
year={2019},
publisher={IEEE}
}

@article{Kang:2019jb,
author = {Kang, Louis and DeWeese, Michael R},
title = {{Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network}},
journal = {eLife},
year = {2019},
volume = {8},
pages = {e46351},
month = nov
}

@article{livezey2019learning,
author = {Jesse A. Livezey and Alejandro F. Bujan and Friedrich T. Sommer},
title = {Learning Overcomplete, Low Coherence Dictionaries with Linear Inference},
journal = {Journal of Machine Learning Research},
year = {2019},
volume = {20},
number = {174},
pages = {1-42},
url = {http://jmlr.org/papers/v20/18-703.html}
}

@article{sachdeva2019heterogeneous,
title={Heterogeneous synaptic weighting improves neural coding in the presence of common noise},
author={Sachdeva, Pratik S and Livezey, Jesse A and DeWeese, Michael R},
journal={bioRxiv},
pages={811364},
year={2019},
publisher={Cold Spring Harbor Laboratory}
}

@misc{li2019learning,
title={Learning Energy-Based Models in High-Dimensional Spaces with Multi-scale Denoising Score Matching},
author={Zengyi Li and Yubei Chen and Friedrich T. Sommer},
year={2019},
eprint={1910.07762},
archivePrefix={arXiv},
primaryClass={stat.ML}
}

@misc{zhang2019word,
title={Word Embedding Visualization Via Dictionary Learning},
author={Juexiao Zhang and Yubei Chen and Brian Cheung and Bruno A Olshausen},
year={2019},
eprint={1910.03833},
archivePrefix={arXiv},
primaryClass={cs.CL}
}

@article{dodds2019spatial,
  title={Spatial whitening in the retina may be necessary for v1 to learn a sparse representation of natural scenes},
  author={Dodds, Eric McVoy and Livezey, Jesse Alexander and DeWeese, Michael Robert},
  journal={BioRxiv},
  pages={776799},
  year={2019},
  publisher={Cold Spring Harbor Laboratory}
}

@article{livezey2019deep,
title={Deep learning as a tool for neural data analysis: speech classification and cross-frequency coupling in human sensorimotor cortex},
author={Livezey, Jesse A and Bouchard, Kristofer E and Chang, Edward F},
journal={PLoS computational biology},
volume={15},
number={9},
pages={e1007091},
year={2019},
publisher={Public Library of Science}
}

@article{Kang:2019ii,
author = {Kang, Louis and Balasubramanian, Vijay},
title = {{A geometric attractor mechanism for self-organization of entorhinal grid modules}},
journal = {eLife},
year = {2019},
volume = {8},
pages = {e46687},
month = aug
}

@phdthesis{paiton2019analysis,
title={Analysis and applications of the locally competitive algorithm},
school={University of California, Berkeley},
author={Paiton, Dylan},
year={2019}
}

@article{dodds2019sparse,
title={On the sparse structure of natural sounds and natural images: similarities, differences, and implications for neural coding},
author={Dodds, Eric McVoy and DeWeese, Michael Robert},
journal={Frontiers in Computational Neuroscience},
volume={13},
pages={39},
year={2019},
url={https://www.frontiersin.org/article/10.3389/fncom.2019.00039},
doi={10.3389/fncom.2019.00039}
}

@article{kent2019resonator,
title={Resonator Networks outperform optimization methods at solving high-dimensional vector factorization},
author={Kent, Spencer J. and Frady, E. Paxon and Sommer, Friedrich T. and Olshausen, Bruno A.},
journal={arXiv preprint, arXiv:1906.11684},
year={2019},
url={https://arxiv.org/abs/1906.11684}
}

@article{mobin2019auditory,
title={Auditory separation of a conversation from background via attentional gating},
author={Mobin, Shariq and Olshausen, Bruno A.},
journal={arXiv preprint, arXiv:1905.10751},
year={2019},
url={https://arxiv.org/abs/1905.10751}
}

@article{livezey2019hangul,
title={Hangul Fonts Dataset: a Hierarchical and Compositional Dataset for Interrogating Learned Representations},
author={Livezey, Jesse A and Hwang, Ahyeon and Bouchard, Kristofer E},
journal={arXiv preprint arXiv:1905.13308},
year={2019}
}

@article{fang2019design,
  title={Design of optical neural networks with component imprecisions},
  author={Fang, Michael Y-S and Manipatruni, Sasikanth and Wierzynski, Casimir and Khosrowshahi, Amir and DeWeese, Michael R},
  journal={Optics express},
  volume={27},
  number={10},
  pages={14009--14029},
  year={2019},
  publisher={Optical Society of America}
}

@article{saremi2019neural,
title={Neural Empirical Bayes},
author={Saremi, Saeed and Hyv{\”a}rinen, Aapo},
journal={arXiv preprint, arXiv:1903.02334},
year={2019},
url={https://arxiv.org/abs/1903.02334}
}

@ARTICLE{frye2019numerically,
author = {{Frye}, Charles G. and {Wadia}, Neha S. and {DeWeese}, Michael R. and
{Bouchard}, Kristofer E.},
title = “{Numerically Recovering the Critical Points of a Deep Linear Autoencoder}”,
journal = {arXiv e-prints},
year = 2019,
month = Jan,
archivePrefix = {arXiv},
eprint = {1901.10603},
}

@article{insanally2019spike,
  title={Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons},
  author={Insanally, Michele N and Carcea, Ioana and Field, Rachel E and Rodgers, Chris C and DePasquale, Brian and Rajan, Kanaka and DeWeese, Michael R and Albanna, Badr F and Froemke, Robert C},
  journal={Elife},
  volume={8},
  year={2019},
  publisher={eLife Sciences Publications, Ltd}
}

@article{frady2019robust,
title = {{Robust computation with rhythmic spike patterns}},
author = {Frady, E Paxon and Sommer, Friedrich T.},
journal = {arXiv preprint arXiv:1901.07718},
month = {jan},
volume = {1901.07718},
year = {2019},
url = {http://arxiv.org/abs/1901.07718}
}

@article {ruebel2019NWB,
title = {NWB:N 2.0: An Accessible Data Standard for Neurophysiology},
author = {Ruebel, Oliver and Tritt, Andrew and Dichter, Benjamin and Braun, Thomas and Cain, Nicholas and Clack, Nathan and Davidson, Thomas J. and Dougherty, Max and Fillion-Robin, Jean-Christophe and Graddis, Nile and Grauer, Michael and Kiggins, Justin T. and Niu, Lawrence and Ozturk, Doruk and Schroeder, William and Soltesz, Ivan and Sommer, Friedrich T. and Svoboda, Karel and Ng, Lydia and Frank, Loren M. and Bouchard, Kristofer},
journal = {bioRxiv},
publisher = {Cold Spring Harbor Laboratory},
year = {2019},
doi = {10.1101/523035},
URL = {https://www.biorxiv.org/content/early/2019/01/17/523035}
}

@inproceedings{paiton2019sparse,
title={Sparse coding protects against adversarial attacks},
author={Paiton, Dylan M and Bowen, Joel and Collins, Jasmine and Frye, Charles and Terekhov, Alex and Olshausen, Bruno},
booktitle={Computational and Systems Neuroscience (CoSyNe 2019)},
year = {2019}
}

@inproceedings{sanborn2019translation,
title={The translation invariant bispectrum for feature analysis in complex cells},
author={Sanborn, Sophia and Zarcone, Ryan and Olshausen, Bruno and Hillar, Christopher},
booktitle={Computational and Systems Neuroscience (CoSyNe 2019)},
year = {2019}
}

@inproceedings{livezey2019theory,
title={A theory of structured noise correlations in peripheral and higher order brain areas and their significance},
author={Livezey, Jesse and Dougherty, Maximillian and Madhow, Sylvia and Sachdeva, Pratik and Bouchard, Kristofer E.},
booktitle={Computational and Systems Neuroscience (CoSyNe 2019)},
year = {2019}
}

@inproceedings{bouchard2019union,
title={Union of Intersections (UoI) for interpretable data driven discovery and prediction in neuroscience},
author={Sachdeva, Pratik and Bhattacharyya, Sharmodeep and Balasubramanian, Mahesh and Ubaru, Shashanka and Bouchard, Kristofer},
booktitle={Computational and Systems Neuroscience (CoSyNe 2019)},
year = {2019}
}

@inproceedings{warner2019cell,
title={Cell assembly model for retinal ganglion cell populations},
author={Warner, Christopher and Sommer, Friedrich},
booktitle={Computational and Systems Neuroscience (CoSyNe 2019)},
year = {2019}
}

@ARTICLE{rahimiEtal2019,
author={A. {Rahimi} and P. {Kanerva} and L. {Benini} and J. M. {Rabaey}},
journal={Proceedings of the IEEE},
title={Efficient Biosignal Processing Using Hyperdimensional Computing: Network Templates for Combined Learning and Classification of ExG Signals},
year={2019},
volume={107},
number={1},
pages={123-143},
keywords={bioelectric potentials;brain;electroencephalography;electromyography;learning (artificial intelligence);medical signal processing;neural nets;neurophysiology;signal classification;biosignal processing;ExG signals classification;HD computing operators;encoded HD vector;domain expert knowledge;brain neural activity;HD network;ExG biosignals;multiclass learning;energy efficiency;one-shot learning;arithmetic operations;versatile set;HD vectors;HD space;neural activity patterns;combined learning;network templates;hyperdimensional computing;Computer architecture;Neural activity;Electromyography;Electroencephalography;Electrodes;Noise measurement;Electrical engineering;Machine learning;Bio-inspired computing;Biosignal classification;brain-inspired computing;brain–machine interface;ECoG;EEG;EMG;error-related potential;hyperdimensional (HD) computing;human–machine interface;interpretable machine learning;motor imagery;network architectures;one-shot learning;seizure detection;vector symbolic architectures},
doi={10.1109/JPROC.2018.2871163},
ISSN={1558-2256},
month={Jan},}

@inproceedings{zheng2018error,
title={Error-Resilient Analog Image Storage and Compression with Analog-Valued RRAM Arrays: An Adaptive Joint Source-Channel Coding Approach},
author={Zheng, Xin and Zarcone, Ryan and Paiton, Dylan and Sohn, Joon and Wan, Weier and Olshausen, Bruno and Wong, H. -S. Phillip},
booktitle={2018 IEEE International Electron Devices Meeting (IEDM)},
pages={3.5.1-3.5.4},
month={Dec},
year={2018},
doi={10.1109/IEDM.2018.8614612},
ISSN={2156-017X}
}

@inproceedings{chen2018sparse,
title={The Sparse Manifold Transform},
author={Chen, Yubei and Paiton, Dylan M. and Olshausen, Bruno A.},
booktitle={Advances in neural information processing systems},
pages = {10534–10545},
year = {2018}
}

@article{mandal2018comment,
  title={Mandal, Klymko, and DeWeese Reply},
  author={Mandal, Dibyendu and Klymko, Katherine and DeWeese, Michael R},
  journal={Physical Review Letters},
  volume={121},
  number={13},
  pages={139802},
  year={2018},
  publisher={APS}
}

@article{mobin2018convolutional,
title={Convolutional vs. Recurrent Neural Networks for Audio Source Separation},
author={Mobin, Shariq and Cheung, Brian and Olshausen, Bruno},
journal={arXiv preprint arXiv:1803.08629},
year={2018}
}

@article{frady2018theory,
title={A theory of sequence indexing and working memory in recurrent neural networks},
author={Frady, E Paxon and Kleyko, Denis and Sommer, Friedrich T},
journal={Neural Computation},
number={30(6)},
pages={1449-1513},
year={2018},
publisher={MIT Press}
}

@article{saremi2018deep,
title={Deep Energy Estimator Networks},
author={Saremi, Saeed and Mehrjou, Arash and Sch{\”o}lkopf, Bernhard and Hyv{\”a}rinen, Aapo},
journal={arXiv preprint arXiv:1805.08306},
year={2018},
url={https://arxiv.org/abs/1805.08306}
}

@inproceedings{anderson18binary,
author = {Alexander. G. Anderson and Cory. P. Berg},
booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)},
title = {The High-Dimensional Geometry of Binary Neural Networks},
year = {2018}
}

@article{bouchard2018international,
title={International neuroscience initiatives through the lens of high-performance computing},
author={Bouchard, Kristofer E and Aimone, James B and Chun, Miyoung and Dean, Thomas and Denker, Michael and Diesmann, Markus and Donofrio, David D and Frank, Loren M and Kasthuri, Narayanan and Koch, Christof and others},
journal={Computer},
volume={51},
number={4},
pages={50–59},
year={2018},
publisher={IEEE}
}

@inproceedings{zarcone2018joint,
title={Joint Source-Channel Coding with Neural Networks for Analog Data Compression and Storage},
author={Zarcone, Ryan and Paiton, Dylan and Anderson, Alex and Engel, Jesse and Wong, HS Philip and Olshausen, Bruno},
booktitle={2018 Data Compression Conference},
year={2018},
organization={IEEE}
}

@article{hillar2018active,
title={Active State Organization of Spontaneous Behavioral Patterns},
author={Hillar, C. and Onnis, G. and Rhea, D. and Tecott, L.},
journal={Nature Scientific Reports},
year={2018},
volume={8},
number={1064}
}

@article{hillar2018robust,
title={Robust Exponential Memory in Hopfield Networks},
author={Hillar, Christopher J. and Tran, Ngoc M.},
journal={The Journal of Mathematical Neuroscience},
year={2018},
volume={8},
number={1},
pages={1}
}

@article{mandal2017entropy,
  title={Entropy production and fluctuation theorems for active matter},
  author={Mandal, Dibyendu and Klymko, Katherine and DeWeese, Michael R},
  journal={Physical review letters},
  volume={119},
  number={25},
  pages={258001},
  year={2017},
  publisher={APS}
}

@Article{rahimi2017hyperdimensional,
title={Hyperdimensional Computing for Blind and One-Shot Classification of EEG Error-Related Potentials},
author={Rahimi, Abbas and Tchouprina, Artiom and Kanerva, Pentti and Mill{\’a}n, Jos{\’e} del R. and Rabaey, Jan M.},
journal={Mobile Networks and Applications},
publisher={ACM (Springer)},
pages={1-12},
year={2017},
month={Oct},
day={03},
issn={1572-8153},
doi={10.1007/s11036-017-0942-6}
}

@article{dunn2017selective,
  title={Selective Insulation of Carbon Nanotubes},
  author={Dunn, Gabriel and Shen, Konlin and Barzegar, Hamid Reza and Shi, Wu and Belling, Jason N and Nguyen, Tran NH and Barkovich, Emil and Chism, Kyle and Maharbiz, Michel M and DeWeese, Michael R and others},
  journal={physica status solidi (b)},
  volume={254},
  number={11},
  pages={1700202},
  year={2017},
  publisher={Wiley Online Library}
}

@article{rahimi2017high,
title={High-dimensional computing as a nanoscalable paradigm},
author={Rahimi, Abbas and Datta, Sohum and Kleyko, Denis and Frady, Edward Paxon and Olshausen, Bruno and Kanerva, Pentti and Rabaey, Jan M},
journal={IEEE Transactions on Circuits and Systems I: Regular Papers},
volume={64},
number={9},
pages={2508–2521},
year={2017},
publisher={IEEE}
}

@article{albanna2017minimum,
title={Minimum and maximum entropy distributions for binary systems with known means and pairwise correlations},
author={Albanna, B. and Hillar, C. and Sohl-Dickstein, J. and DeWeese, M.},
journal={Entropy},
volume={19},
number={8},
pages={427},
year={2017},
publisher={Multidisciplinary Digital Publishing Institute}
}

@inproceedings{bouchard2017sparse,
title={Sparse coding of ECoG signals identifies interpretable components for speech control in human sensorimotor cortex},
author={Bouchard, Kristofer E and Bujan, Alejandro F and Chang, Edward F and Sommer, Friedrich T},
booktitle={39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
pages={3636–3639},
year={2017},
organization={IEEE}
}

@article{olshausen2017sparse,
title={Sparse codes from memristor grids},
author={Olshausen, Bruno A and Rozell, Christopher J},
journal={Nature nanotechnology},
volume={12},
number={8},
pages={722},
year={2017},
publisher={Nature Publishing Group}
}

@article{mehrjou2017annealed,
title={Annealed Generative Adversarial Networks},
author={Mehrjou, Arash and Sch{\”o}lkopf, Bernhard and Saremi, Saeed},
journal={arXiv preprint arXiv:1705.07505},
year={2017}
}

@inproceedings{cheung2017emergence,
title={Emergence of foveal image sampling from learning to attend in visual scenes},
author={Cheung, Brian and Weiss, Eric and Olshausen, Bruno},
booktitle={International Conference on Learning Representations (ICLR)},
year={2017}
}

@inproceedings{hillar2017revisiting,
title={Revisiting Perceptual Distortion for Natural Images: Mean Discrete Structural Similarity Index},
author={Hillar, Christopher and Marzen, Sarah},
booktitle={Data Compression Conference (DCC), 2017},
pages={241–249},
year={2017},
organization={IEEE}
}

@article{hillar2017neural,
title={Neural network coding of natural images with applications to pure mathematics},
author={Hillar, Christopher J and Marzen, Sarah E},
journal={Algebraic and Geometric Methods in Discrete Mathematics},
volume={685},
pages={189},
year={2017},
publisher={American Mathematical Soc.}
}

@article{engel2017opportunities,
title={Opportunities for analog coding in emerging memory systems},
author={Engel, Jesse H. and Eryilmaz, S. Burc and Kim, SangBum and BrightSky, Matthew and Lam, Chung and Lung, Hsiang-Lan and Olshausen, Bruno A. and Wong, H.-S. Philip},
journal={arXiv preprint arXiv:1701.06063},
year={2017}
}

@article{marzen2016weak,
title={Weak universality in sensory tradeoffs},
author={Marzen, Sarah and DeDeo, Simon},
journal={Physical Review E},
volume={94},
number={6},
year={2016}
}

@inproceedings{anderson2016neural,
title={A neural model of high-acuity vision in the presence of fixational eye movements},
author={Anderson, Alexander G and Olshausen, Bruno A and Ratnam, Kavitha and Roorda, Austin},
booktitle={Signals, Systems and Computers, 2016 50th Asilomar Conference on},
pages={588–592},
year={2016},
organization={IEEE}
}

@inproceedings{joshi2016language,
title={Language geometry using random indexing},
author={Joshi, Aditya and Halseth, Johan T and Kanerva, Pentti},
booktitle={International Symposium on Quantum Interaction},
pages={265–274},
year={2016},
organization={Springer}
}

@article{marzen2016predictive,
title={Predictive rate-distortion for infinite-order Markov processes},
author={Marzen, Sarah E and Crutchfield, James P},
journal={Journal of Statistical Physics},
volume={163},
number={6},
pages={1312–1338},
year={2016},
publisher={Springer}
}

@article{anderson2016deepmovie,
title={DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies},
author={Anderson, Alexander G and Berg, Cory P and Mossing, Daniel P and Olshausen, Bruno A},
journal={arXiv preprint arXiv:1605.08153},
year={2016}
}

@article{mandal2016nonequilibrium,
  title={Nonequilibrium work energy relation for non-Hamiltonian dynamics},
  author={Mandal, Dibyendu and DeWeese, Michael R},
  journal={Physical Review E},
  volume={93},
  number={4},
  pages={042129},
  year={2016},
  publisher={APS}
}

@article{berdyyeva2016direct,
title={Direct imaging of hippocampal epileptiform calcium motifs following kainic acid administration in freely behaving mice},
author={Berdyyeva, Tamara K and Frady, E Paxon and Nassi, Jonathan J and Aluisio, Leah and Cherkas, Yauheniya and Otte, Stephani and Wyatt, Ryan M and Dugovic, Christine and Ghosh, Kunal K and Schnitzer, Mark J and Lovenberg, Timothy and Bonaventure, Pascal},
journal={Frontiers in neuroscience},
volume={10},
pages={53},
year={2016},
publisher={Frontiers}
}

@article{teeters2015neurodata,
title={Neurodata without borders: creating a common data format for neurophysiology},
author={Teeters, Jeffery L and Godfrey, Keith and Young, Rob and Dang, Chinh and Friedsam, Claudia and Wark, Barry and Asari, Hiroki and Peron, Simon and Li, Nuo and Peyrache, Adrien and others},
journal={Neuron},
volume={88},
number={4},
pages={629–634},
year={2015},
publisher={Elsevier}
}

@article{hillar2015can,
title={When can dictionary learning uniquely recover sparse data from subsamples?},
author={Hillar, Christopher J and Sommer, Friedrich T},
journal={IEEE Transactions on Information Theory},
volume={61},
number={11},
pages={6290–6297},
year={2015},
publisher={IEEE}
}

@inproceedings{laiho2015high,
title={High-dimensional computing with sparse vectors},
author={Laiho, Mika and Poikonen, Jussi H and Kanerva, Pentti and Lehtonen, Eero},
booktitle={2015 IEEE Biomedical Circuits and Systems Conference (BioCAS)},
pages={1–4},
year={2015},
organization={IEEE}
}

@inproceedings{effenberger2015discovery,
title={Discovery of salient low-dimensional dynamical structure in neuronal population activity using hopfield networks},
author={Effenberger, Felix and Hillar, Christopher},
booktitle={International Workshop on Similarity-Based Pattern Recognition},
pages={199–208},
year={2015},
organization={Springer}
}

@article{berger2015markov,
  title={A Markov jump process for more efficient Hamiltonian Monte Carlo},
  author={Berger, Andrew B and Mudigonda, Mayur and DeWeese, Michael R and Sohl-Dickstein, Jascha},
  journal={arXiv preprint arXiv:1509.03808},
  year={2015}
}

@article{zulkowski2015optimal,
  title={Optimal control of overdamped systems},
  author={Zulkowski, Patrick R and DeWeese, Michael R},
  journal={Physical Review E},
  volume={92},
  number={3},
  pages={032117},
  year={2015},
  publisher={APS}
}

@article{zulkowski2015optimalb,
  title={Optimal protocols for slowly driven quantum systems},
  author={Zulkowski, Patrick R and DeWeese, Michael R},
  journal={Physical Review E},
  volume={92},
  number={3},
  pages={032113},
  year={2015},
  publisher={APS}
}

@inproceedings{mehta2015exploring,
title={Exploring discrete approaches to lossy compression schemes for natural image patches},
author={Mehta, Ram and Marzen, Sarah and Hillar, Christopher},
booktitle={Signal Processing Conference (EUSIPCO), 2015 23rd European},
pages={2236–2240},
year={2015},
organization={IEEE}
}

@article{marzen2015time,
title={Time resolution dependence of information measures for spiking neurons: Scaling and universality},
author={Marzen, Sarah E and DeWeese, Michael R and Crutchfield, James P},
journal={Frontiers in computational neuroscience},
volume={9},
year={2015},
publisher={Frontiers Media SA}
}

@article{hillar2015robust,
title={Robust discovery of temporal structure in multi-neuron recordings using Hopfield networks},
author={Hillar, Christopher and Effenberger, Felix},
journal={Procedia Computer Science},
volume={53},
pages={365–374},
year={2015},
publisher={Elsevier}
}

@article{marzen2015informational,
title={Informational and causal architecture of discrete-time renewal processes},
author={Marzen, Sarah E and Crutchfield, James P},
journal={Entropy},
volume={17},
number={7},
pages={4891–4917},
year={2015},
publisher={Multidisciplinary Digital Publishing Institute}
}

@article{carels2015rats,
title={Rats Exert Executive Control},
author={Carels, Vanessa M and DeWeese, Michael R},
journal={Neuron},
volume={86},
number={6},
pages={1324–1326},
year={2015},
publisher={Elsevier}
}

@article{sohl2015device,
title={A device for human ultrasonic echolocation},
author={Sohl-Dickstein, Jascha and Teng, Santani and Gaub, Benjamin M and Rodgers, Chris C and Li, Crystal and DeWeese, Michael R and Harper, Nicol S},
journal={IEEE Transactions on Biomedical Engineering},
volume={62},
number={6},
pages={1526–1534},
year={2015},
publisher={IEEE}
}

@article{crutchfield2015signatures,
title={Signatures of infinity: Nonergodicity and resource scaling in prediction, complexity, and learning},
author={Crutchfield, James P and Marzen, Sarah},
journal={Physical Review E},
volume={91},
number={5},
pages={050106},
year={2015},
publisher={APS}
}

@inproceedings{cheung2015discovering,
title={Discovering Hidden Factors of Variation in Deep Networks},
author={Cheung, B. and Livezey, J.A. and Bansal, A.K. and Olshausen, B.A.},
booktitle={International Conference on Learning Representations (ICLR 2015), Workshop},
year={2015}
}

@article{sprague2015stereopsis,
title={Stereopsis is adaptive for the natural environment},
author={Sprague, William W and Cooper, Emily A and To{\v{s}}i{\’c}, Ivana and Banks, Martin S},
journal={Science Advances},
volume={1},
number={4},
pages={e1400254},
year={2015},
publisher={American Association for the Advancement of Science}
}

@article{hillar2015hadamard,
title={A Hadamard-type lower bound for symmetric diagonally dominant positive matrices},
author={Christopher J. Hillar and Andre Wibisono},
journal={Linear Algebra and its Applications},
volume={472},
pages={135 – 141},
year={2015}
}

@article{hagen2015visapy,
title={ViSAPy: A Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms},
author={Hagen, Espen and Ness, Torbj{\o}rn V and Khosrowshahi, Amir and S{\o}rensen, Christina and Fyhn, Marianne and Hafting, Torkel and Franke, Felix and Einevoll, Gaute T},
journal={Journal of neuroscience methods},
volume={245},
pages={182–204},
year={2015},
publisher={Elsevier}
}

@article{sohl2015deep,
title={Deep unsupervised learning using nonequilibrium thermodynamics},
author={Sohl-Dickstein, Jascha and Weiss, Eric A and Maheswaranathan, Niru and Ganguli, Surya},
journal={arXiv preprint arXiv:1503.03585},
year={2015}
}

@article{crutchfield2014understanding,
title={Understanding and Designing Complex Systems: Response to “A framework for optimal high-level descriptions in science and engineering–preliminary report”},
author={Crutchfield, James P. and James, Ryan G. and Marzen, Sarah and Varn, Dowman P.},
journal={arXiv preprint arXiv:1412.8520},
year={2014}
}

@inproceedings{engel2014capacity,
title={Capacity optimization of emerging memory systems: A shannon-inspired approach to device characterization},
author={Engel, Jesse H and Eryilmaz, S Burc and Kim, SangBum and BrightSky, Matthew and Lam, Chung and Lung, Hsiang-Lan and Olshausen, Bruno A and Wong, H-S Philip},
booktitle={Electron Devices Meeting (IEDM), 2014 IEEE International},
pages={29–4},
year={2014},
organization={IEEE}
}

@inproceedings{fletcher2014scalable,
title={Scalable inference for neuronal connectivity from calcium imaging},
author={Fletcher, Alyson K and Rangan, Sundeep},
booktitle={Advances in Neural Information Processing Systems},
pages={2843–2851},
year={2014}
}

@inproceedings{mobin2014information,
title={Information-based learning by agents in unbounded state spaces},
author={Mobin, Shariq A and Arnemann, James A and Sommer, Friedrich},
booktitle={Advances in Neural Information Processing Systems},
pages={3023–3031},
year={2014}
}

@article{harper2014neural,
title={The neural code for auditory space depends on sound frequency and head size in an optimal manner},
author={Harper, Nicol S and Scott, Brian H and Semple, Malcolm N and McAlpine, David},
journal={PloS one},
volume={9},
number={11},
pages={e108154},
year={2014},
publisher={Public Library of Science}
}

@incollection{olshausen2014perception,
title={Perception as an inference problem},
author={Olshausen, Bruno A},
booktitle={The Cognitive Neurosciences V},
editor={Gazzaniga, M. and Mangun, R.},
year={2014},
publisher={MIT Press},
address={Cambridge, MA}
}

@inproceedings{hillar2014hopfield,
title={A hopfield recurrent neural network trained on natural images performs state-of-the-art image compression},
author={Hillar, Christopher and Mehta, Ram and Koepsell, Kilian},
booktitle={Image Processing (ICIP), 2014 IEEE International Conference on},
pages={4092–4096},
year={2014},
organization={IEEE}
}

@inproceedings{kanerva2014computing,
title={Computing with 10,000-bit words},
author={Kanerva, Pentti},
booktitle={Communication, Control, and Computing (Allerton), 2014 52nd Annual Allerton Conference on},
pages={304–310},
year={2014},
organization={IEEE}
}

@article{marzen2014information,
title={Information anatomy of stochastic equilibria},
author={Marzen, Sarah and Crutchfield, James P},
journal={Entropy},
volume={16},
number={9},
pages={4713–4748},
year={2014},
publisher={Multidisciplinary Digital Publishing Institute}
}

@article{koster2014modeling,
title={Modeling higher-order correlations within cortical microcolumns},
author={K{\”o}ster, Urs and Sohl-Dickstein, Jascha and Gray, Charles M and Olshausen, Bruno A},
journal={PLoS computational biology},
volume={10},
number={7},
pages={e1003684},
year={2014},
publisher={Public Library of Science}
}

@inproceedings{sohl2014hamiltonian,
title={Hamiltonian Monte Carlo Without Detailed Balance},
author={Sohl-Dickstein, Jascha and Mudigonda, Mayur and DeWeese, Michael},
booktitle={International Conference on Machine Learning},
pages={719–726},
year={2014}
}

@article{rodgers2014neural,
title={Neural correlates of task switching in prefrontal cortex and primary auditory cortex in a novel stimulus selection task for rodents},
author={Rodgers, Chris C and DeWeese, Michael R},
journal={Neuron},
volume={82},
number={5},
pages={1157–1170},
year={2014},
publisher={Elsevier}
}

@article{zulkowski2014optimal,
title={Optimal finite-time erasure of a classical bit},
author={Zulkowski, Patrick R and DeWeese, Michael R},
journal={Physical Review E},
volume={89},
number={5},
pages={052140},
year={2014},
publisher={APS}
}

@article{knoblauch2014structural,
title={Structural synaptic plasticity has high memory capacity and can explain graded amnesia, catastrophic forgetting, and the spacing effect},
author={Knoblauch, Andreas and K{\”o}rner, Edgar and K{\”o}rner, Ursula and Sommer, Friedrich T},
journal={PLoS One},
volume={9},
number={5},
pages={e96485},
year={2014},
publisher={Public Library of Science}
}

@article{agarwal2014spatially,
title={Spatially distributed local fields in the hippocampus encode rat position},
author={Agarwal, Gautam and Stevenson, Ian H and Ber{\’e}nyi, Antal and Mizuseki, Kenji and Buzs{\’a}ki, Gy{\”o}rgy and Sommer, Friedrich T},
journal={Science},
volume={344},
number={6184},
pages={626–630},
year={2014},
publisher={American Association for the Advancement of Science}
}

@article{tosic2014learning,
title={Learning joint intensity-depth sparse representations},
author={Tosic, Ivana and Drewes, Sarah},
journal={IEEE Transactions on Image Processing},
volume={23},
number={5},
pages={2122–2132},
year={2014},
publisher={IEEE}
}

@article{mizuseki2014neurosharing,
title={Neurosharing: large-scale data sets (spike, LFP) recorded from the hippocampal-entorhinal system in behaving rats},
author={Mizuseki, Kenji and Diba, Kamran and Pastalkova, Eva and Teeters, Jeff and Sirota, Anton and Buzs{\’a}ki, Gy{\”o}rgy},
journal={F1000Research},
volume={3},
year={2014},
publisher={Faculty of 1000 Ltd}
}

@article{lewicki2014scene,
title={Scene analysis in the natural environment},
author={Lewicki, Michael S and Olshausen, Bruno A and Surlykke, Annemarie and Moss, Cynthia F},
journal={Frontiers in psychology},
volume={5},
year={2014},
publisher={Frontiers Media SA}
}

@article{martinez2014statistical,
title={Statistical wiring of thalamic receptive fields optimizes spatial sampling of the retinal image},
author={Martinez, Luis M and Molano-Maz{\’o}n, Manuel and Wang, Xin and Sommer, Friedrich T and Hirsch, Judith A},
journal={Neuron},
volume={81},
number={4},
pages={943–956},
year={2014},
publisher={Elsevier}
}

@article{zulkowski2013optimal,
title={Optimal control of transitions between nonequilibrium steady states},
author={Zulkowski, Patrick R and Sivak, David A and DeWeese, Michael R},
journal={PloS one},
volume={8},
number={12},
pages={e82754},
year={2013},
publisher={Public Library of Science}
}

@inproceedings{mudigonda2013learning,
title={Learning non-local features for classification using compressed sensing and sparse coding},
author={Mudigonda, M. and Muller, N. and Joshi, A. and Hillar, C. and Sommer, F.},
booktitle={Advances in Neural Information Processing Systems (NIPS 2013), Workshop},
year={2013}
}

@article{koster2013testing,
title={Testing our conceptual understanding of V1 function},
author={K{\”o}ster, Urs and Olshausen, Bruno},
journal={arXiv preprint arXiv:1311.0778},
year={2013}
}

@article{hillar2013most,
title={Most tensor problems are NP-hard},
author={Hillar, Christopher J and Lim, Lek-Heng},
journal={Journal of the ACM (JACM)},
volume={60},
number={6},
pages={45},
year={2013},
publisher={ACM}
}

@incollection{olshausen2013natural,
title={What Natural Scene Statistics Can Tell Us about Cortical Representation},
author={Olshausen, Bruno A},
booktitle={The New Visual Neurosciences},
editor={Werner, John S. and Chalupa, Leo M.},
year={2013},
publisher={MIT Press},
address={Cambridge, MA}
}

@incollection{sommer2013neural,
title={Neural oscillations and synchrony as mechanisms for coding, communication and computation in the visual system},
author={Sommer, Friedrich},
booktitle={The New Visual Neurosciences},
editor={Werner, John S. and Chalupa, Leo M.},
year={2013},
publisher={MIT Press},
address={Cambridge, MA}
}

@incollection{sommer2013inhibitory,
title={Inhibitory circuits in the visual thalamus},
author={Hirsch, J.A. and Wang, X. and Vaingankar, V. and Sommer, F.T.},
booktitle={The New Visual Neurosciences},
editor={Werner, John S. and Chalupa, Leo M.},
year={2013},
publisher={MIT Press},
address={Cambridge, MA}
}

@article{zylberberg2013sparse,
title={Sparse coding models can exhibit decreasing sparseness while learning sparse codes for natural images},
author={Zylberberg, Joel and DeWeese, Michael Robert},
journal={PLoS computational biology},
volume={9},
number={8},
pages={e1003182},
year={2013},
publisher={Public Library of Science}
}

@article{little2013maximal,
title={Maximal mutual information, not minimal entropy, for escaping the “Dark Room”},
author={Little, Daniel Ying-Jeh and Sommer, Friedrich Tobias},
journal={Behavioral and Brain Sciences},
volume={36},
number={3},
pages={220–221},
year={2013},
publisher={Cambridge University Press}
}

@incollection{agarwal2013measuring,
title={Measuring information in spike trains about intrinsic brain signals},
author={Agarwal, Gautam and Sommer, Friedrich},
booktitle={Spike Timing: Mechanisms and Function},
editor={DiLorenzo, Patricia M. and Victor, Jonathan D.},
year={2013},
publisher={CRC Press},
address={Boca Raton, FL}
}

@article{hromadka2013up,
title={Up states are rare in awake auditory cortex},
author={Hrom{\’a}dka, Tom{\’a}{\v{s}} and Zador, Anthony M and DeWeese, Michael R},
journal={Journal of Neurophysiology},
volume={109},
number={8},
pages={1989–1995},
year={2013},
publisher={Am Physiological Soc}
}

@article{king2013inhibitory,
title={Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1},
author={King, Paul D and Zylberberg, Joel and DeWeese, Michael R},
journal={Journal of Neuroscience},
volume={33},
number={13},
pages={5475–5485},
year={2013},
publisher={Soc Neuroscience}
}

@article{little2013learning,
title={Learning and exploration in action-perception loops},
author={Little, Daniel Y and Sommer, Friedrich T},
journal={Frontiers in neural circuits},
volume={7},
year={2013},
publisher={Frontiers Media SA}
}

@inproceedings{olshausen2013highly,
title={Highly overcomplete sparse coding},
author={Olshausen, Bruno A},
booktitle={SPIE Human Vision and Electronic Imaging XVIII},
volume={8651},
year={2013}
}

@article{hillar2013maximum,
title={Maximum entropy distributions on graphs},
author={Hillar, Christopher and Wibisono, Andre},
journal={arXiv preprint arXiv:1301.3321},
year={2013}
}

@article{zylberberg2012dead,
title={Dead leaves and the dirty ground: Low-level image statistics in transmissive and occlusive imaging environments},
author={Zylberberg, Joel and Pfau, David and DeWeese, Michael Robert},
journal={Physical Review E},
volume={86},
number={6},
pages={066112},
year={2012},
publisher={APS}
}

@inproceedings{hillar2012efficient,
title={Efficient and optimal binary Hopfield associative memory storage using minimum probability flow},
author={Hillar, C. and Sohl-Dickstein, J. and Koepsell, K.},
booktitle={Advances in Neural Information Processing Systems (NIPS 2012), workshop on Discrete Optimization in Machine Learning},
year={2012}
}

@inproceedings{theis2012training,
title={Training sparse natural image models with a fast Gibbs sampler of an extended state space},
author={Theis, Lucas and Sohl-Dickstein, Jascha and Bethge, Matthias},
booktitle={Advances in Neural Information Processing Systems},
pages={1124–1132},
year={2012}
}

@article{vaingankar2012neurons,
title={Neurons in the thalamic reticular nucleus are selective for diverse and complex visual features},
author={Vaingankar, Vishal and Soto-Sanchez, Cristina and Wang, Xin and Sommer, Friedrich T and Hirsch, Judith A},
journal={Frontiers in integrative neuroscience},
volume={6},
year={2012},
publisher={Frontiers Media SA}
}

@article{abbey2012non,
title={Non-Gaussian statistical properties of breast images},
author={Abbey, Craig K and Nosratieh, Anita and Sohl-Dickstein, Jascha and Yang, Kai and Boone, John M},
journal={Medical physics},
volume={39},
number={11},
pages={7121–7130},
year={2012},
publisher={Wiley Online Library}
}

@article{zulkowski2012geometry,
title={Geometry of thermodynamic control},
author={Zulkowski, Patrick R and Sivak, David A and Crooks, Gavin E and DeWeese, Michael R},
journal={Physical Review E},
volume={86},
number={4},
pages={041148},
year={2012},
publisher={APS}
}

@article{hillar2012comment,
title={Comment on the article “Distilling free-form natural laws from experimental data”},
author={Hillar, Christopher and Sommer, Friedrich},
journal={arXiv preprint arXiv:1210.7273},
year={2012}
}

@incollection{olshausen201320,
title={20 years of learning about vision: Questions answered, questions unanswered, and questions not yet asked},
author={Olshausen, Bruno A},
booktitle={20 Years of Computational Neuroscience},
pages={243–270},
year={2013},
publisher={Springer}
}

@article{still2012thermodynamics,
title={Thermodynamics of prediction},
author={Still, Susanne and Sivak, David A and Bell, Anthony J and Crooks, Gavin E},
journal={Physical review letters},
volume={109},
number={12},
pages={120604},
year={2012},
publisher={APS}
}

@article{carlson2012sparse,
title={Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus},
author={Carlson, Nicole L and Ming, Vivienne L and DeWeese, Michael Robert},
journal={PLoS computational biology},
volume={8},
number={7},
pages={e1002594},
year={2012},
publisher={Public Library of Science}
}

@article{cadieu2012learning,
title={Learning intermediate-level representations of form and motion from natural movies},
author={Cadieu, Charles F and Olshausen, Bruno A},
journal={Neural computation},
volume={24},
number={4},
pages={827–866},
year={2012},
publisher={MIT Press}
}

@article{canolty2012detecting,
title={Detecting event-related changes of multivariate phase coupling in dynamic brain networks},
author={Canolty, Ryan T and Cadieu, Charles F and Koepsell, Kilian and Ganguly, Karunesh and Knight, Robert T and Carmena, Jose M},
journal={Journal of neurophysiology},
volume={107},
number={7},
pages={2020–2031},
year={2012},
publisher={Am Physiological Soc}
}

@Inbook{Sommer2012,
author={Sommer, Friedrich T.},
editor={Seel, Norbert M.},
title={Associative Memory and Learning},
bookTitle={Encyclopedia of the Sciences of Learning},
year={2012},
publisher={Springer US},
address={Boston, MA},
pages={340–342}
}

@article{canolty2012multivariate,
title={Multivariate Phase–Amplitude cross-frequency coupling in neurophysiological signals},
author={Canolty, Ryan T and Cadieu, Charles F and Koepsell, Kilian and Knight, Robert T and Carmena, Jose M},
journal={IEEE Transactions on Biomedical Engineering},
volume={59},
number={1},
pages={8–11},
year={2012},
publisher={IEEE}
}

@phdthesis{khosrowshahi2011laminar,
title={The laminar organization of V1 neural activity in response to dynamic natural scenes},
school={University of California, Berkeley},
author={Khosrowshahi, Amir},
year={2011}
}

@article{sohl-dickstein2011new,
title={New method for parameter estimation in probabilistic models: minimum probability flow},
author={Sohl-Dickstein, Jascha and Battaglino, Peter B and DeWeese, Michael R},
journal={Physical review letters},
volume={107},
number={22},
pages={220601},
year={2011},
publisher={APS}
}

@inproceedings{culpepper2011building,
title={Building a better probabilistic model of images by factorization},
author={Culpepper, Benjamin J and Sohl-Dickstein, Jascha and Olshausen, Bruno A},
booktitle={Computer Vision (ICCV), 2011 IEEE International Conference on},
year={2011},
organization={IEEE}
}

@article{wang2011inhibitory,
title={Inhibitory circuits for visual processing in thalamus},
author={Wang, Xin and Sommer, Friedrich T and Hirsch, Judith A},
journal={Current opinion in neurobiology},
volume={21},
number={5},
pages={726–733},
year={2011},
publisher={Elsevier}
}

@article{zylberberg2011sparse,
title={A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of V1 simple cell receptive fields},
author={Zylberberg, Joel and Murphy, Jason Timothy and DeWeese, Michael Robert},
journal={PLoS computational biology},
volume={7},
number={10},
pages={e1002250},
year={2011},
publisher={Public Library of Science}
}

@article{toˇsic2011learning,
title={Learning sparse representations of depth},
author={Tošić , Ivana and Olshausen, Bruno A and Culpepper, Benjamin J},
journal={IEEE journal of selected topics in signal processing},
volume={5},
number={5},
pages={941–952},
year={2011},
publisher={IEEE}
}

@article{charles2011learning,
title={Learning sparse codes for hyperspectral imagery},
author={Charles, Adam S and Olshausen, Bruno A and Rozell, Christopher J},
journal={IEEE Journal of Selected Topics in Signal Processing},
volume={5},
number={5},
pages={963–978},
year={2011},
publisher={IEEE}
}

@inproceedings{sohl-dickstein2011minimum,
author={Jascha Sohl-Dickstein and Peter Battaglino and Michael DeWeese},
title={Minimum Probability Flow Learning},
booktitle={Proceedings of the 28th International Conference on Machine Learning (ICML-11)},
series={ICML ’11},
year={2011},
editor={Lise Getoor and Tobias Scheffer},
location={Bellevue, Washington, USA},
isbn={978-1-4503-0619-5},
month={June},
publisher={ACM},
address={New York, NY, USA},
pages={905–912},
}

@article{zylberberg2011should,
title={How should prey animals respond to uncertain threats?},
author={Zylberberg, Joel and DeWeese, Michael Robert},
journal={Frontiers in computational neuroscience},
volume={5},
year={2011},
publisher={Frontiers Media SA}
}

@inproceedings{wang2011lie,
title={Lie group transformation models for predictive video coding},
author={Wang, Ching Ming and Shol-Dickstein, Jascha and Tošić , Ivana and Olshausen, Bruno A},
booktitle={Data Compression Conference (DCC), 2011},
pages={83–92},
year={2011},
organization={IEEE}
}

@article{wang2011thalamic,
title={Thalamic interneurons and relay cells use complementary synaptic mechanisms for visual processing},
author={Wang, Xin and Vaingankar, Vishal and Sanchez, Cristina Soto and Sommer, Friedrich T and Hirsch, Judith A},
journal={Nature neuroscience},
volume={14},
number={2},
pages={224–231},
year={2011},
publisher={Nature Research}
}

@article{lauritzen2010effects,
title={The effects of visuospatial attention measured across visual cortex using source-imaged, steady-state EEG},
author={Lauritzen, Thomas Z and Ales, Justin M and Wade, Alex R},
journal={Journal of vision},
volume={10},
number={14},
pages={39–39},
year={2010},
publisher={The Association for Research in Vision and Ophthalmology}
}

@article{cadieu2010phase,
title={Phase coupling estimation from multivariate phase statistics},
author={Cadieu, Charles F and Koepsell, Kilian},
journal={Neural computation},
volume={22},
number={12},
pages={3107–3126},
year={2010},
publisher={MIT Press}
}

@inproceedings{isely2010deciphering,
title={Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication},
author={Isely, Guy and Hillar, Christopher and Sommer, Fritz},
booktitle={Advances in neural information processing systems},
pages={910–918},
year={2010}
}

@inproceedings{garrigues2010group,
title={Group sparse coding with a laplacian scale mixture prior},
author={Garrigues, Pierre and Olshausen, Bruno A},
booktitle={Advances in neural information processing systems},
pages={676–684},
year={2010}
}

@article{olshausen2010does,
title={Does the brain de-jitter retinal images?},
author={Olshausen, Bruno A and Anderson, Charles H},
journal={Proceedings of the National Academy of Sciences},
volume={107},
number={46},
pages={19607–19608},
year={2010},
publisher={National Acad Sciences}
}

@inproceedings{kanerva2010what,
title={What we mean when we say “What’s the dollar of Mexico?”: Prototypes and mapping in concept space},
author={Kanerva, Pentti},
booktitle={2010 AAAI fall symposium series},
year={2010}
}

@article{wang2010recoding,
title={Recoding of sensory information across the retinothalamic synapse},
author={Wang, Xin and Hirsch, Judith A and Sommer, Friedrich T},
journal={Journal of Neuroscience},
volume={30},
number={41},
pages={13567–13577},
year={2010},
publisher={Soc Neuroscience}
}

@article{canolty2010oscillatory,
title={Oscillatory phase coupling coordinates anatomically dispersed functional cell assemblies},
author={Canolty, Ryan T and Ganguly, Karunesh and Kennerley, Steven W and Cadieu, Charles F and Koepsell, Kilian and Wallis, Jonathan D and Carmena, Jose M},
journal={Proceedings of the National Academy of Sciences},
volume={107},
number={40},
pages={17356–17361},
year={2010},
publisher={National Acad Sciences}
}

@article{koepsell2010exploring,
title={Exploring the function of neural oscillations in early sensory systems},
author={Koepsell, Kilian and Wang, Xin and Hirsch, Judith A and Sommer, Friedrich T},
journal={Frontiers in neuroscience},
volume={4},
year={2010},
publisher={Frontiers Media SA}
}

@inproceedings{coulter2010adaptive,
title={Adaptive compressed sensing—a new class of self-organizing coding models for neuroscience},
author={Coulter, William K and Hillar, Christopher J and Isley, Guy and Sommer, Friedrich T},
booktitle={Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on},
pages={5494–5497},
year={2010},
organization={IEEE}
}

@article{olshausen2010applied,
title={Applied mathematics: The statistics of style},
author={Olshausen, Bruno A and DeWeese, Michael R},
journal={Nature},
volume={463},
number={7284},
pages={1027–1028},
year={2010},
publisher={Nature Publishing Group}
}

@inproceedings{silver2010isolating,
title={Isolating human brain functional connectivity associated with a specific cognitive process},
author={Silver, Michael A and Landau, Ayelet N and Lauritzen, Thomas Z and Prinzmetal, William and Robertson, Lynn C},
booktitle={Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series},
volume={7527},
pages={7},
year={2010}
}

@article{knoblauch2010memory,
title={Memory capacities for synaptic and structural plasticity},
author={Knoblauch, Andreas and Palm, G{\”u}nther and Sommer, Friedrich T},
journal={Neural Computation},
volume={22},
number={2},
pages={289–341},
year={2010},
publisher={MIT Press}
}

@article{sohl2010unsupervised,
title={An unsupervised algorithm for learning lie group transformations},
author={Sohl-Dickstein, Jascha and Wang, Ching Ming and Olshausen, Bruno A},
journal={arXiv preprint arXiv:1001.1027},
year={2010}
}

@article{tsao2010object,
title={Object Recognition: Physiology and Computational Insights},
author={Tsao, Doris Y. and Cadieu, Charles F. and Livingstone, Margaret S.},
journal={Primate Neuroethology},
year={2010}
}

@inproceedings{culpepper2009learning,
title={Learning transport operators for image manifolds},
author={Culpepper, Benjamin and Olshausen, Bruno A},
booktitle={Advances in neural information processing systems},
pages={423–431},
year={2009}
}

@article{monaci2009learning,
title={Learning bimodal structure in audio–visual data},
author={Monaci, Gianluca and Vandergheynst, Pierre and Sommer, Friedrich T},
journal={IEEE Transactions on Neural Networks},
volume={20},
number={12},
pages={1898–1910},
year={2009},
publisher={IEEE}
}

@article{lauritzen2009top,
title={Top–down flow of visual spatial attention signals from parietal to occipital cortex},
author={Lauritzen, Thomas Z and D’Esposito, Mark and Heeger, David J and Silver, Michael A},
journal={Journal of vision},
volume={9},
number={13},
pages={18–18},
year={2009},
publisher={The Association for Research in Vision and Ophthalmology}
}

@inproceedings{cadieu2009learning,
title={Learning transformational invariants from natural movies},
author={Cadieu, Charles and Olshausen, Bruno A},
booktitle={Advances in neural information processing systems},
pages={209–216},
year={2009}
}

@article{parra2009maximization,
title={On the maximization of information flow between spiking neurons},
author={Parra, Lucas C and Beck, Jeffrey M and Bell, Anthony J},
journal={Neural Computation},
volume={21},
number={11},
pages={2991–3009},
year={2009},
publisher={MIT Press}
}

@article{ming2009efficient,
title={Efficient coding in human auditory perception},
author={Ming, Vivienne L and Holt, Lori L},
journal={The Journal of the Acoustical Society of America},
volume={126},
number={3},
pages={1312–1320},
year={2009},
publisher={ASA}
}

@inproceedings{olshausen2009learning,
title={Learning real and complex overcomplete representations from the statistics of natural images},
author={Olshausen, Bruno A and Cadieu, Charles F and Warland, David K},
booktitle={SPIE},
volume={7446},
year={2009}
}

@article{kanerva2009hyperdimensional,
title={Hyperdimensional computing: An introduction to computing in distributed representation with high-dimensional random vectors},
author={Kanerva, Pentti},
journal={Cognitive Computation},
volume={1},
number={2},
pages={139–159},
year={2009},
publisher={Springer}
}

@article{koepsell2009retinal,
title={Retinal oscillations carry visual information to cortex},
author={Koepsell, Kilian and Wang, Xin and Vaingankar, Vishal and Wei, Yichun and Wang, Qingbo and Rathbun, Daniel L and Usrey, W Martin and Hirsch, Judith A and Sommer, Friedrich T},
journal={Frontiers in systems neuroscience},
volume={3},
year={2009},
publisher={Frontiers Media SA}
}

@inproceedings{abbey2009higher,
author = {K. Abbey, Craig and Sohl-Dickstein, Jascha and A. Olshausen, Bruno and P. Eckstein, Miguel and M. Boone, John},
year = {2009},
month = {02},
title = {Higher-order scene statistics of breast images},
volume = {7263},
booktitle = {Progress in Biomedical Optics and Imaging – Proceedings of SPIE}
}

@inproceedings{garrigues2008homotopy,
title={An homotopy algorithm for the Lasso with online observations},
author={Garrigues, Pierre and Ghaoui, Laurent E},
booktitle={Advances in neural information processing systems},
pages={489–496},
year={2008}
}

@article{yang2008millisecond,
title={Millisecond-scale differences in neural activity in auditory cortex can drive decisions},
author={Yang, Yang and DeWeese, Michael R and Otazu, Gonzalo H and Zador, Anthony M},
journal={Nature neuroscience},
volume={11},
number={11},
pages={1262–1263},
year={2008},
publisher={Nature Publishing Group}
}

@article{koepsell2008information,
title={Information transmission in oscillatory neural activity},
author={Koepsell, Kilian and Sommer, Friedrich T},
journal={Biological cybernetics},
volume={99},
number={4-5},
pages={403},
year={2008},
publisher={Springer}
}

@article{rozell2008sparse,
title={Sparse coding via thresholding and local competition in neural circuits},
author={Rozell, Christopher J and Johnson, Don H and Baraniuk, Richard G and Olshausen, Bruno A},
journal={Neural computation},
volume={20},
number={10},
pages={2526–2563},
year={2008},
publisher={MIT Press}
}

@article{koepsell2008neuroscience,
title={Neuroscience and the Study of Literature: Some Thoughts on the Possibility of Transferring Knowledge},
author={Koepsell, Kilian and Spoerhase, Carlos},
journal={JLT Articles},
volume={2},
number={2},
year={2008}
}

@inproceedings{monaci2008learning,
title={Learning sparse generative models of audiovisual signals},
author={Monaci, Gianluca and Sommer, Friedrich T and Vandergheynst, Pierre},
booktitle={Signal Processing Conference, 2008 16th European},
pages={1–5},
year={2008},
organization={IEEE}
}

@article{teeters2008data,
title={Data sharing for computational neuroscience},
author={Teeters, Jeffrey L and Harris, Kenneth D and Millman, K Jarrod and Olshausen, Bruno A and Sommer, Friedrich T},
journal={Neuroinformatics},
volume={6},
number={1},
pages={47–55},
year={2008},
publisher={Springer}
}

@article{hromadka2008sparse,
title={Sparse representation of sounds in the unanesthetized auditory cortex},
author={Hrom{\’a}dka, Tom{\’a}{\v{s}} and DeWeese, Michael R and Zador, Anthony M},
journal={PLoS biology},
volume={6},
number={1},
pages={e16},
year={2008},
publisher={Public Library of Science}
}

@inproceedings{garrigues2007learning,
title={Learning horizontal connections in a sparse coding model of natural images},
author={Garrigues, Pierre and Olshausen, Bruno A},
booktitle={Advances in Neural Information Processing Systems},
pages={505–512},
year={2007}
}

@article{wang2007feedforward,
title={Feedforward excitation and inhibition evoke dual modes of firing in the cat’s visual thalamus during naturalistic viewing},
author={Wang, Xin and Wei, Yichun and Vaingankar, Vishal and Wang, Qingbo and Koepsell, Kilian and Sommer, Friedrich T and Hirsch, Judith A},
journal={Neuron},
volume={55},
number={3},
pages={465–478},
year={2007},
publisher={Elsevier}
}

@MISC{sommer2007bunte,
author={Sommer, Friedrich},
title={Bunte Theorien für graue Zellen},
editor={Spektrum.de},
month={May},
year={2007},
note = {\href{http://http://www.spektrum.de/magazin/bunte-theorien-fuer-graue-zellen/872207/}{Spektrum.de} {[Online; posted 18-May-2007]}},
}

@article{rehn2007network,
title={A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields},
author={Rehn, Martin and Sommer, Friedrich T},
journal={Journal of computational neuroscience},
volume={22},
number={2},
pages={135–146},
year={2007},
publisher={Springer}
}

@inproceedings{olshausen2007bilinear,
title={Bilinear models of natural images},
author={Olshausen, Bruno A and Cadieu, Charles and Culpepper, Jack and Warland, David K},
booktitle={Human Vision and Electronic Imaging XII},
volume={6492},
pages={649206},
year={2007},
organization={International Society for Optics and Photonics}
}

@article{deweese2006non,
title={Non-Gaussian membrane potential dynamics imply sparse, synchronous activity in auditory cortex},
author={DeWeese, Michael R and Zador, Anthony M},
journal={Journal of Neuroscience},
volume={26},
number={47},
pages={12206–12218},
year={2006},
publisher={Soc Neuroscience}
}

@article{rehn2006storing,
title={Storing and restoring visual input with collaborative rank coding and associative memory},
author={Rehn, Martin and Sommer, Friedrich T},
journal={Neurocomputing},
volume={69},
number={10},
pages={1219–1223},
year={2006},
publisher={Elsevier}
}

@article{bethge2006factorial,
title={Factorial coding of natural images: how effective are linear models in removing higher-order dependencies?},
author={Bethge, Matthias},
journal={JOSA A},
volume={23},
number={6},
pages={1253–1268},
year={2006},
publisher={Optical Society of America}
}

@article{sommer2006neural,
author = {Sommer, Friedrich and Kanerva, Pentti},
year = {2006},
month = {02},
pages = {86 – 87},
title = {Can neural models of cognition benefit from the advantages of connectionism?},
volume = {29},
booktitle = {Behavioral and Brain Sciences}
}

@inproceedings{bell2005maximising,
title={Maximising sensitivity in a spiking network},
author={Bell, Anthony J and Parra, Lucas C},
booktitle={Advances in neural information processing systems},
pages={121–128},
year={2005}
}

@article{olshausen2005close,
title={How close are we to understanding V1?},
author={Olshausen, Bruno A and Field, David J},
journal={Neural computation},
volume={17},
number={8},
pages={1665–1699},
year={2005},
publisher={MIT Press}
}

@article{sommer2005synfire,
title={Synfire chains with conductance-based neurons: internal timing and coordination with timed input},
author={Sommer, Friedrich T and Wennekers, Thomas},
journal={Neurocomputing},
volume={65},
pages={449–454},
year={2005},
publisher={Elsevier}
}

@article{george2005computing,
title={Computing with inter-spike interval codes in networks of integrate and fire neurons},
author={George, Dileep and Sommer, Friedrich T},
journal={Neurocomputing},
volume={65},
pages={415–420},
year={2005},
publisher={Elsevier}
}

@article{martinez2005receptive,
title={Receptive field structure varies with layer in the primary visual cortex},
author={Martinez, Luis M and Wang, Qingbo and Reid, R Clay and Pillai, Cinthi and Alonso, Jos{\’e}-Ma{\~n}uel and Sommer, Friedrich T and Hirsch, Judith A},
journal={Nature neuroscience},
volume={8},
number={3},
pages={372–379},
year={2005},
publisher={Nature Publishing Group}
}