9.641 Neural Networks
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The lectures are all taped, and are available in RealVideo format. Each lecture is linked below, but if you'd like to download them, they're here.
Lecture schedule
- Lecture 1 (2/1): From spikes to rates
(Postscript, PDF,
realvideo)
- Lecture 2 (2/3): Perceptrons: simple and multilayer
(realvideo)
- Lecture 3 (2/8): Perceptrons as models of vision
(realvideo)
- D. Marr, Vision, Section
2.2, 54-79, W.H. Freeman and Company, New York (1982).
- D.H. Hubel, Eye, Brain, and Vision,
Chapter 3,
39-46, Scientific American Library, New York, (1988-1995).
-
Lenet website
- Lecture 4 (2/10): Linear networks
(realvideo)
- Lecture 5 (2/15): Retina
(realvideo)
- E.H. Adelson, Lightness
Perception and Lightness Illusions, In The New Cognitive
Neurosciences, 2nd ed., M. Gazzaniga, ed. Cambridge, MA: MIT Press,
pp. 339-351, (2000).
- H. K. Hartline and F. Ratliff,
Inhibitory Interaction in the Retina of Limulus.
Physiology of Photoreceptor Organs, Ed. M.G.F. Fuortes,
382-447, Springer-Verlag, Berlin, Heidelberg, New York (1972)
- Lecture 6 (2/17): Lateral inhibition and feature selectivity
(slides 1, slides 2, slides 3, realvideo)
- W. H. Press et al., Numerical Recipes
in C, 2d ed., Chaps. 12 and 13.
- G. Strang, Introduction to Applied Mathematics,
Section 4.2, 290-309, Wellesley-Cambridge Press, Wellesley, Massachusetts (1986).
- Lecture 7 (2/24): Objectives and optimization (realvideo)
- Lecture 8 (3/1): Hybrid analog-digital computation, ring network (realvideo)
- R. Hahnloser, R. Sarpeshkar, M. Mahowald, R.J. Douglas, H.S. Seung,
Digital
selection and analog amplification coexist in a cortex-inspired silicon circuit, Nature, 405, 947-51, 2000.
- Richard H. R. Hahnloser, H. Sebastian Seung, Jean-Jacques Slotine: Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks. Neural Computation 2003.
- Lecture 9 (3/3): Constraint satisfaction, stereopsis (realvideo)
- Lecture 10 (3/8): Bidirectional perception (realvideo)
- Lecture 11 (3/10): Signal reconstruction (realvideo)
- Lecture 12 (3/15): Hamiltonian dynamics (slides, realvideo)
- Midterm (3/17)
- Lecture 13 (3/29): Antisymmetric networks (slides, realvideo)
- Lecture 14 (3/31): Excitatory-Inhibitory networks, learning (slides, realvideo)
- Lecture 15 (4/5): Associative memory (realvideo)
- Lecture 16 (4/7): Models of delay activity, Integrators (realvideo)
- Lecture 17 (4/12): Multistability, Clustering (realvideo)
- Lecture 18 (4/14): VQ and PCA (slides 1, slides 2, realvideo)
- Lecture 19 (4/21): More PCA, Delta rule (slides, realvideo)
- Lecture 20 (4/26): Conditioning and Backpropagation (slides 1, slides 2, realvideo)
- Lecture 21 (4/28): More Backpropagation (slides, realvideo)
- Lecture 22 (5/3): Stochastic Gradient Descent (realvideo)
- Lecture 23 (5/5): Reinforcement Learning (realvideo)
- Lecture 24 (5/10): More Reinforcement Learning (realvideo)
- Lecture 25 (5/12): Final Review (realvideo)
Last Updated on Wednesday, 21-Dec-2005 16:08:04 EST .