| Part 1: Neurons and Synapses | | |
W 1/19 | 1. Introduction and Overview |
NIH Brain Facts (chapter 1)
| |
F 1/21 | Math and Matlab Tutorial (optional) |
Trappenberg Math Appendix
| |
M 1/24 | 2. Neurons and Membranes |
Trappenberg Ch 1.1-2.2 | |
W 1/26 | 3. Spikes and Cables | Trappenberg Ch 2 (C) | HW1 out |
M 1/31 | 4. Synapse and Dendrites | Trappenberg Ch 3.1, 3.3 | |
W 2/2 | 5. Synaptic plasticity | Trappenberg Ch 4
Abbott and Nelson (2000)
| |
M 2/7 | 6. Hebbian Learning | Trappenberg Ch 4, HPK Ch 8
| |
W 2/9 | 7. Logical Computation |
Trappenberg 3.1,3.5
F. Rosenblatt - Perceptron.
McCulloch and Pitts (1943)
| HW2 out, HW1 in |
| Part 2: Representation and Computation | | |
M 2/14 | 8. Principal Component Analysis |
Oja (1982)
| |
W 2/16 | 9. Source Separation |
Foldiak (1990)
| |
M 2/21 | 10. Sparse Coding |
Olshausen and Field (1997)
(2004)
| |
W 2/23 | 11. Deep Belief Net |
Trappenberg Ch 10.3
Hinton and Salahutdinov (2006)
| HW3 out. Hw2 in. |
M 2/28 | 12. Computational Maps | HPK Ch 9. Trappenberg 7.1-7.2
Kohonen (1982)
| |
W 3/2 | Midterm |
| |
3/4-3/11 | Midsemester and Spring break. No Journal Club |
| March 7. Midterm grade due |
| PART 3: Neural Networks | | |
M 3/14 | 13. Visual System |
Trappenberg 5.1.
Van Essen et al (1992)
Fellman and Van Essen ( 1991)
| |
W 3/16 | 14. Markov Network |
Marr and Poggio (1976)
Samonds et al. (2013)
Wang et al. (2018)
| Term Project Proposal in |
M 3/21 | 15. Attractor network and Memory | Trappenberg Ch 8. Ch 9.4
Hopfield and Tank (1986)
| |
W 3/23 | 16. Cue Integration | | HW4 out, HW3 in |
M 3/28 | 17. Neural network (MLP) |
Trappenberg Ch 6, 10.1.
Fukushima (1988),
Krizhevsky et al. (2012)
| |
W 3/30 | 18. Convolutional Neural Networks |
Zeiler and Fergus (2013)
LeCun, Bengio and Hinton (2015)
| |
M 4/4 | 19. Deep Network and the Brain |
Yamins and DiCarlo (2016)
Maheswaranathan et al. (2018)
Lillicrap et al. (2016)
| |
| PART 4: PREDICTION AND FEEDBACK | | |
W 4/6 | 20. Biological Plausible Learning |
Arrout et al. (2019),
Guerguiev et al. (2017)
| HW5 out, HW4 in. |
F 4/9 | Carnival No Journal Club | | |
M 4/11 | 21. Hierarchical Inference |
Mumford (1992)
Rao and Ballard (1998)
Lee and Mumford (2003)
| |
W 4/13 | 22. Attention and Self-Attention |
Trappenberg Ch 10.
Vaswani et al. (2017)
Lindsay (2020)
Knudsen (2007)
| |
M 4/18 | 23. Prediction and Surprise |
Trappenberg Ch 10.
Lotter et al (2016),
Colah (2015)
Rao (2015)
| |
W 4/20 | 24. Probabilistic Inference |
Weiss et al. (2002).
Ma et al. (2006)
Kersten and Yuille (2003)
| HW 5 in. |
M 4/25 | 25. Inference Mechanisms |
Orban et al. (2016).
Shivkumar et al. (2019)
| |
W 4/27 | 26. Reinforcement Learning |
Trappenberg. Ch 9.
Niv (2009),
Montague et al. (1996)
| |
M 5/2 | Final Exam Period | | |
Th 5/12 | Final Grade due 4 p.m. | | |