AS.050.375, AS.050.675

Probabilistic Models of the Visual Cortex:
 
Tues/Thurs: 9:00-10:15am Fall 2019, Krieger 170.
 
 

Course Description

The course gives an introduction to computational models of the mammalian visual cortex. It covers topics in low-, mid-, and high-level vision. It briefly discusses the relevant evidence from anatomy, electrophysiology, imaging (e.g., fMRI), and psychophysics. It concentrates on mathematical modelling of these phenomena taking into account recent progress in probabilistic models of computer vision and developments in machine learning.

Reading and Background Material

Grading Plan: 5 homework assignments will be posed on blackboard (roughly biweekly).

Homework 1, submission link will be updated soon.

Preliminary Schedule (subject to revision)

Lecture Date Topics

Handouts

Required Reading Optional Reading
1

Sept-3

Introduction (Part I)
Slides YuilleKersten (Section 1.1, 1.2, 1.3)
2
Sept-5
Introduction (Part II) - How Biological Vision Can Help AI Vision
Slides
J. Tenenbaum et al. 2017 Bialek   EyeSmarter
  Microprocessor   VisualCrowding
3

Sept-10

Introduction to Retina and Primary Visual Cortex (V1)
Retina V1 V1_Mike_May Lecture by Clay Reid
4
Sept-12
Linear Filtering
Slides YuilleKersten (Section 2.1)
5

Sept-17

Sparsity and Hebbian Learning
YuilleKersten (Section 2.2)
6
Sept-19 Filters for Binocular Stereo and Motion
YuilleKersten (Section 2.4)
7

Sept-24

Regression, Nonlinearity and Neural Networks
8

Sept-26

TBD
9
Oct-1
Context and Spatial Interactions Between Neurons I
10
Oct-3
Context and Spatial Interactions Between Neurons II
11
Oct-8
Context Examples: Weak Membrane, Associative Field
12
Oct-10
Introduction to Deep Networks
13
Oct-15
Boltzmann Machines & More Context Examples
14
Oct-17
Cue Coupling

15
Oct-22
More Cue Coupling
16
Oct-24
Deep Networks for Cue Coupling
17
Oct-29
Perceptrons
18
Oct-31
What do Deep Networks do?

19
Nov-5
Unsupervised Learning
20
Nov-7
Attention (Bottom-Up)
21
Nov-12
Compositionality (I)

22
Nov-14
Compositionality (II)


Nov-19
Thanksgiving



Nov-21
Thanksgiving


23
Nov-26
Vision and Language

24
Nov-28
High Level Vision

25
Dec-3
Kalman Filtering
26
Dec-5
Review of Course