VS265: Reading Fall2010: Difference between revisions

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(Updated the dates back to what they were for Fall 2010)
 
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==== 27 Aug ====
==== 26 Aug ====
* Dreyfus, H.L. and Dreyfus, S.E. [http://redwood.berkeley.edu/vs265/DreyfusDreyfus.pdf ''Making a Mind vs. Modeling the Brain: Artificial Intelligence Back at a Branchpoint'']. Daedalus, Winter 1988.
* Dreyfus, H.L. and Dreyfus, S.E. [http://redwood.berkeley.edu/vs265/DreyfusDreyfus.pdf ''Making a Mind vs. Modeling the Brain: Artificial Intelligence Back at a Branchpoint'']. Daedalus, Winter 1988.
* Bell, A.J. ''Levels and loops: the future of artificial intelligence and neuroscience''. Phil Trans: Bio Sci. '''354''':2013--2020 (1999) [http://dx.doi.org/10.1098/rstb.1999.0540 here] or [http://www.cnl.salk.edu/~tony/ptrsl.pdf here]
* Bell, A.J. ''Levels and loops: the future of artificial intelligence and neuroscience''. Phil Trans: Bio Sci. '''354''':2013--2020 (1999) [http://dx.doi.org/10.1098/rstb.1999.0540 here] or [http://www.cnl.salk.edu/~tony/ptrsl.pdf here]
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* Land, MF and Fernald, RD. [http://redwood.berkeley.edu/vs265/landfernald92.pdf The Evolution of Eyes], Ann Revs Neuro, 1992.
* Land, MF and Fernald, RD. [http://redwood.berkeley.edu/vs265/landfernald92.pdf The Evolution of Eyes], Ann Revs Neuro, 1992.


==== 29 Aug ====
==== 31 Aug ====
* Mead, C. [http://redwood.berkeley.edu/vs265/Mead.pdf Chapter 1: Introduction] and [http://redwood.berkeley.edu/vs265/Neurons.pdf Chapter 4: Neurons] from ''Analog VLSI and Neural Systems'', Addison-Wesley, 1989.
* Mead, C. [http://redwood.berkeley.edu/vs265/Mead.pdf Chapter 1: Introduction] and [http://redwood.berkeley.edu/vs265/Neurons.pdf Chapter 4: Neurons] from ''Analog VLSI and Neural Systems'', Addison-Wesley, 1989.
* [http://redwood.berkeley.edu/vs265/lti-conv/lti-convolution.html Linear time-invariant systems and convolution]
* [http://redwood.berkeley.edu/vs265/lti-conv/lti-convolution.html Linear time-invariant systems and convolution]

Latest revision as of 02:55, 28 August 2012

26 Aug

Optional:

31 Aug

02 Sep

07 Sep

  • Handout on supervised learning in single-stage feedforward networks
  • 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

21 Sep

Optional:

28 Sep

Optional readings:

5 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].

7 Oct

Additional reading:

12/14 Oct

19 Oct (David Zipser guest lecture)

  • manual for David Zipser's BPTT simulator

26 Oct

2/4 Nov

  • HKP Chapter 7, section 7.1

Application to neural data analysis:

16 Nov

18 Nov

23 Nov

Chapter 4 will be emailed to the class.

2 Dec (Jeff Hawkins guest lecture)

7 Dec (Paul Rhodes guest lecture)

9 Dec (Pentti Kanerva guest lecture)