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Difference between revisions of "VS265: Reading"

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(30 Oct)
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* From Clay Reid's lab, [http://www.nature.com/nature/journal/v433/n7026/abs/nature03274.html Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex]. Make sure you look at the supplementary material and videos on their web site (seems partly broken) [http://reid.med.harvard.edu/movies.html].
 
* From Clay Reid's lab, [http://www.nature.com/nature/journal/v433/n7026/abs/nature03274.html Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex]. Make sure you look at the supplementary material and videos on their web site (seems partly broken) [http://reid.med.harvard.edu/movies.html].
  
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==== 6 Nov ====
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* [http://redwood.berkeley.edu/vs265/tenenbaum-manifold.pdf A Global Geometric Framework for Nonlinear Dimensionality Reduction ], Tenenbaum et al., Science 2000.
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* [http://redwood.berkeley.edu/vs265/roweis-saul-manifold.pdf Nonlinear Dimensionality Reduction by Locally Linear Embedding], Roweis and Saul, Science 2000.
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* [http://redwood.berkeley.edu/vs265/carlsson-ijcv08.pdf On the Local Behavior of Spaces of Natural Images], Carlsson et al., Int J Comput Vis (2008) 76: 1–12.
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Additional reading:
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* [http://redwood.berkeley.edu/vs265/webster-face-adaptation.pdf Adaptation to natural facial categories], Michael A. Webster, Daniel Kaping, Yoko Mizokami & Paul Duhamel, Nature, 2004.
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* [http://redwood.berkeley.edu/vs265/leopold.pdf Prototype-referenced shape encoding revealed by high-level aftereffects], David A. Leopold, Alice J. O’Toole, Thomas Vetter and Volker Blanz, Nature, 2001.
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* [http://redwood.berkeley.edu/vs265/Blanz-siggraph-99.pdf A Morphable Model For The Synthesis Of 3D Faces], Blanz & Vetter 1999.
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* [http://mbthompson.com/research/ Matthew B. Thompson's web page on flashed face distortion effect]
  
  

Revision as of 22:51, 4 November 2014

Aug 28: Introduction

Optional:

Sept 2: Neuron models

Background reading on dynamics, linear time-invariant systems and convolution, and differential equations:

Sept 4: Linear neuron, Perceptron

Background on linear algebra:

Sept 11: Multicompartment models, dendritic integration (Rhodes guest lecture)

Sept. 16, 18: Supervised learning

  • HKP Chapters 5, 6
  • Handout on supervised learning in single-stage feedforward networks
  • Handout on supervised learning in multi-layer feedforward networks - "back propagation"

Further reading:

Sept. 23, 24: Unsupervised learning

  • HKP Chapters 8 and 9, DJCM chapter 36, DA chapter 8, 10
  • Handout: Hebbian learning and PCA
  • PDP Chapter 9 (full text of Michael Jordan's tutorial on linear algebra, including section on eigenvectors)

Optional:

Sept 30, Oct 2: Attractor Networks and Associative Memories (Sommer guest lectures)

  • "HKP" Chapter 2 and 3 (sec. 3.3-3.5), 7 (sec. 7.2-7.3), DJCM chapter 42, DA chapter 7
  • Handout on attractor networks - their learning, dynamics and how they differ from feed-forward networks
  • Hopfield82
  • Hopfield84
  • Willshaw69

Oct 7: Ecological utility and the mythical neural code (Feldman guest lecture)

  • Feldman10 Ecological utility and the mythical neural code

Oct 9: Hyperdimensional computing (Kanerva guest lecture)

Oct 16: Structural and Functional Connectomics (Tom Dean guest lecture)

21,23,28 Oct

Additional readings:

30 Oct, 4 Nov

Optional:

6 Nov

Additional reading:


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