Lec # | Topics | READINGS |
---|---|---|
1 | From Spikes to Rates | ![]() Ermentrout, Bard. "Reduction of Conductance-Based Models with Slow Synapses to Neural Nets." Neural Computation 6, no. 4 (July 1994): 679-695. |
2 | Perceptrons: Simple and Multilayer | |
3 | Perceptrons as Models of Vision | ![]() ![]() LeNet Web site |
4 | Linear Networks | |
5 | Retina | ![]() ![]() |
6 | Lateral Inhibition and Feature Selectivity | ![]() ![]() |
7 | Objectives and Optimization | |
8 | Hybrid Analog-Digital Computation Ring Network | Hahnloser, R. H., R. Sarpeshkar, M. A. Mahowald, R. J. Douglas, and H. S. Seung. "Digital selection and analog amplification coexist in a cortex-inspired silicon circuit." Nature 405, no. 6789 (June 22, 2000): 947-51. Hahnloser, Richard H., H. Sebastian Seung, and Jean-Jacques Slotine. "Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks." Neural Computation 15, no. 3 (March 2003): 621-38. |
9 | Constraint Satisfaction Stereopsis | |
10 | Bidirectional Perception | |
11 | Signal Reconstruction | |
12 | Hamiltonian Dynamics | |
Midterm | ||
13 | Antisymmetric Networks | |
14 | Excitatory-Inhibitory Networks Learning | |
15 | Associative Memory | |
16 | Models of Delay Activity Integrators | |
17 | Multistability Clustering | |
18 | VQ PCA | |
19 | More PCA Delta Rule | |
20 | Conditioning Backpropagation | |
21 | More Backpropagation | |
22 | Stochastic Gradient Descent | |
23 | Reinforcement Learning | |
24 | More Reinforcement Learning | |
25 | Final Review |