VS265: Reading Fall2012: Difference between revisions

From RedwoodCenter
Jump to navigationJump to search
No edit summary
m (Bruno moved page VS265: Reading to VS265: Reading Fall2012 without leaving a redirect)
 
(10 intermediate revisions by the same user not shown)
Line 110: Line 110:
* [http://redwood.berkeley.edu/vs265/info-theory.pdf Information theory primer]  
* [http://redwood.berkeley.edu/vs265/info-theory.pdf Information theory primer]  
* [http://redwood.berkeley.edu/vs265/handout-sparse-08.pdf Sparse coding and ICA handout]
* [http://redwood.berkeley.edu/vs265/handout-sparse-08.pdf Sparse coding and ICA handout]
* Bell and Sejnowski, [http://redwood.berkeley.edu/vs265/tony-ica.pdf An Information-Maximization Approach to Blind Separation and Blind Deconvolution], Neural Comp, 1995.
* Jascha Sohl-Dickstein, [http://redwood.berkeley.edu/vs265/jascha-natgrad.pdf Natural gradients made quick and dirty]
* Jascha Sohl-Dickstein, [http://redwood.berkeley.edu/vs265/jascha-cookbook.pdf Natural gradient cookbook]
* Bell & Sejnowski, [http://redwood.berkeley.edu/vs265/tony-ica.pdf An Information-Maximization Approach to Blind Separation and Blind Deconvolution], Neural Comp, 1995.
* Karklin & Simoncelli, [[http://redwood.berkeley.edu/vs265/karklin-simoncelli.pdf Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons], NIPS 2011.
* Hyvarinen, Hoyer, Inki, [http://redwood.berkeley.edu/vs265/TICA.pdf Topographic Independent Component Analysis], Neural Comp, 2001.
* Hyvarinen, Hoyer, Inki, [http://redwood.berkeley.edu/vs265/TICA.pdf Topographic Independent Component Analysis], Neural Comp, 2001.
* Karklin & Lewicki paper on  [http://redwood.berkeley.edu/vs265/karklin-lewicki2003.pdf Learning Higher-Order Structure in Natural Images], Network 2003.
* Karklin & Lewicki paper on  [http://redwood.berkeley.edu/vs265/karklin-lewicki2003.pdf Learning Higher-Order Structure in Natural Images], Network 2003.
* Shao & Cottrell paper on [http://redwood.berkeley.edu/vs265/hshan-nips06.pdf Recursive ICA], NIPS 2006.
* Shao & Cottrell paper on [http://redwood.berkeley.edu/vs265/hshan-nips06.pdf Recursive ICA], NIPS 2006.
==== 26 Nov ====
* Robbie Jacobs' [http://www.bcs.rochester.edu/people/robbie/jacobslab/cheat_sheet/sensoryIntegration.pdf notes on Kalman filter]
* [http://redwood.berkeley.edu/vs265/kalman.m kalman.m] demo script
* Greg Welch's [http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html  tutorial on Kalman filter]
* [http://vision.ucla.edu/~doretto/projects/dynamic-textures.html Dynamic texture models]
* Kevin Murphy's [http://redwood.berkeley.edu/vs265/murphy-hmm.pdf  HMM tutorial]
==== 28 Nov ====
* Chris Eliasmith, Charlie Anderson, [http://books.google.com/books?id=J6jz9s4kbfIC Neural Engineering:  Computation, Representation, and Dynamics in Neurobiological Systems], MIT Press, 2004.
Chapter 4 will be emailed to the class.
* Softky and Koch, [http://redwood.berkeley.edu/vs265/softky-koch-jn93.pdf The Highly Irregular Firing of Cortical Cells Is Inconsistent with Temporal Integration of Random EPSPs], J Neuroscience, January 1993, 13(1):334-350.
* Mainen and Sejnowski, [http://redwood.berkeley.edu/vs265/mainen-sejnowski.pdf Reliability of Spike Timing in Neocortical Neurons], Science, Vol 268, 6 June 1995.
* Shadlen and Newsome, [http://redwood.berkeley.edu/vs265/shadlen-newsome1.pdf Noise, neural codes and cortical organization], Curr Opin in Neur, 1994, 4:569-579.
* Shadlen and Newsom, [http://redwood.berkeley.edu/vs265/shadlen-newsome1.pdf Is there a signal in the noise?], Current Opin in Neur, 1995, 5:248-250.
* Softky, [http://redwood.berkeley.edu/vs265/softky-commentary.pdf Simple codes versus efficient codes], Current Opin in Neuro, 1995, 5:239-247.
* Izhikevich, [http://redwood.berkeley.edu/vs265/izhikevich-nn03.pdf Simple model of spiking neurons], IEEE Trans Neur Networks, 14(6):2003.
* Izhikevich, [http://redwood.berkeley.edu/vs265/izhikevich-which-nn04.pdf Which Model to Use for Cortical Spiking Neurons?], IEEE Trans Neur Networks, 15(5):2004.
==== 3 Dec ====
David Zipser guest lecture:
* HKP section 7.3
* [http://redwood.berkeley.edu/vs265/zipser-manual.pdf BPTT manual]
==== 5 Dec ====
Pentti Kanerva guest lecture:
* Kanerva, [http://redwood.berkeley.edu/vs265/kanerva09-hyperdimensional.pdf Hyperdimensional Computing]

Latest revision as of 18:47, 28 August 2014

27 Aug

29 Aug

Optional:

05 Sep

17 Sep

  • Handout on supervised learning in multi-layer feedforward networks - "backpropagation"
  • Y. LeCun, L. Bottou, G. Orr, and K. Muller (1998) "Efficient BackProp," in Neural Networks: Tricks of the trade, (G. Orr and Muller K., eds.).
  • NetTalk demo

24 Sep

Optional:

8 Oct

Optional readings:

15 Oct

Here are some additional links to papers mentioned in lecture. Optional reading:

- Gary Blasdel, Orientation selectivity, preference, and continuity in monkey striate cortex., J Neurosci, 1992. Another source of many of nice images are in the galleries on Amiram Grinvald's site: [1]

- From Clay Reid's lab, Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Make sure you look at the supplementary material and videos on their web site (seems partly broken) [2].

22 Oct

Additional reading:

24 Oct

29 Oct

Chris Hillar guest lecture:

5 Nov

19 Nov

  • HKP Chapter 7, section 7.1 (Boltzmann machines)

Application to neural data analysis:

21 Nov

26 Nov

28 Nov

Chapter 4 will be emailed to the class.

3 Dec

David Zipser guest lecture:

5 Dec

Pentti Kanerva guest lecture: