Courses

Fall 2021

Neuroscience 299: Computing with High-Dimensional Vectors - Fall 2021

This seminar will introduce an emerging computing framework that is based on using high-dimensional vectors to represent and manipulate symbols, data structures, and functions. In recent years, there have been an increasing number of applications in perception, analogical reasoning, models of memory, and language processing. These applications in turn can help us understand how these functions are performed by distributed networks of neurons in the brain.

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Spring 2021

The Art of Modeling - Spring 2021

While models are central to scientific practice, modeling remains a surprisingly individual process that relies on the inclinations and ingenuity of the investigator. In this course we will attempt to identify what constitutes a good model by examining general perspectives on modeling practice and specific case studies of successful models, as well as modeling our own data sets.

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Fall 2020

VS265: Neural Computation - Fall 2020

This course provides an introduction to the theory of neural computation, especially as it pertains to vision. Topics include neural network models, learning rules, associative memory models, recurrent networks, and models of neural coding in the brain.

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Fall 2018

VS265: Neural Computation - Fall 2018

This course provides an introduction to the theory of neural computation. Topics include neural network models, supervised and unsupervised learning rules, associative memory models, recurrent networks, probabilistic/graphical models, and models of neural coding in the brain.

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Summer 2018

CRCNS Course on Mining and Modeling of Neuroscience Data

This course introduces the major open questions of neuroscience and teaches state-of–the-art techniques for analyzing and modeling neuroscience data sets.

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Summer 2017

CRCNS Course on Mining and Modeling of Neuroscience Data

This course introduces the major open questions of neuroscience and teaches state-of–the-art techniques for analyzing and modeling neuroscience data sets.

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Summer 2015

CRCNS Course on Mining and Modeling of Neuroscience Data

This course introduces the major open questions of neuroscience and teaches state-of–the-art techniques for analyzing and modeling neuroscience data sets.

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Spring 2015

VS298: Visual Perception and its Neural Substrates

This is a seminar course that attempts to examine and unite the psychophysical and neural coding theory literature in the context of visual perception.

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Fall 2014

VS298: Unsolved Problems in Vision

The goal of this seminar course is to step back and ask, what are the important problems that remain unsolved in vision research, and how should these be approached empirically?

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VS265: Neural Computation

This course provides an introduction to the theory of neural computation. Topics include neural network models, supervised and unsupervised learning rules, associative memory models, recurrent networks, probabilistic/graphical models, and models of neural coding in the brain.

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Spring 2014

VS298: Natural Scene Statistics

This seminar examines what is known about the statistical structure of natural visual and auditory scenes, and theories of how sensory coding strategies have been adapted to this structure.

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Fall 2012

VS265: Neural Computation

This seminar examines what is known about the statistical structure of natural visual and auditory scenes, and theories of how sensory coding strategies have been adapted to this structure.

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Spring 2012

VS298: Animal Eyes

This seminar will survey the wide variety of eye designs and visual systems found in the animal kingdom.

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Summer 2011

CRCNS Course on Mining and Modeling of Neuroscience Data

This course introduces the major open questions of neuroscience and teaches state-of–the-art techniques for analyzing and modeling neuroscience data sets.

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Fall 2010

VS265: Neural Computation

This seminar examines what is known about the statistical structure of natural visual and auditory scenes, and theories of how sensory coding strategies have been adapted to this structure.

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Fall 2008

VS298: Neural Computation

This seminar examines what is known about the statistical structure of natural visual and auditory scenes, and theories of how sensory coding strategies have been adapted to this structure.

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Fall 2006

VS298: Neural Computation

This seminar examines what is known about the statistical structure of natural visual and auditory scenes, and theories of how sensory coding strategies have been adapted to this structure.

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