Introduction to Neural Networks

Calendar

Lec #	Topics	Key DATES
1	From Spikes to Rates
2	Perceptrons: Simple and Multilayer
3	Perceptrons as Models of Vision
4	Linear Networks	Problem set 1 due
5	Retina
6	Lateral Inhibition and Feature Selectivity	Problem set 2 due
7	Objectives and Optimization	Problem set 3 due
8	Hybrid Analog-Digital Computation Ring Network
9	Constraint Satisfaction Stereopsis	Problem set 4 due
10	Bidirectional Perception
11	Signal Reconstruction	Problem set 5 due
12	Hamiltonian Dynamics
	Midterm
13	Antisymmetric Networks
14	Excitatory-Inhibitory Networks Learning
15	Associative Memory
16	Models of Delay Activity Integrators	Problem set 6 due one day after Lec #16
17	Multistability Clustering
18	VQ PCA	Problem set 7 due
19	More PCA Delta Rule	Problem set 8 due
20	Conditioning Backpropagation
21	More Backpropagation	Problem set 9 due
22	Stochastic Gradient Descent
23	Reinforcement Learning	Problem set 10 due
24	More Reinforcement Learning
25	Final Review
	Final Exam