VS265: Slides: Difference between revisions
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==== Oct 30, Nov. 4, 6 ==== | ==== Oct 30, Nov. 4, 6 ==== | ||
* [https://archive.org/details/VS265-Oct30 Oct30 Video] | * [https://archive.org/details/VS265-Oct30 Oct30 Video] | ||
* [https://archive.org/details/VS265-Fall14-Nov4 Nov4 Video] | |||
* [https://archive.org/details/VS265-Fall14-Nov6 Nov6 Video] | |||
* [https://archive.org/details/VS265-Nov13-Fall2014 Nov 13 Video] | |||
* [http://redwood.berkeley.edu/vs265/som-lecture.pdf Self-organizing maps] | * [http://redwood.berkeley.edu/vs265/som-lecture.pdf Self-organizing maps] | ||
* [http://redwood.berkeley.edu/vs265/manifold-models-lecture.pdf Manifold models] | * [http://redwood.berkeley.edu/vs265/manifold-models-lecture.pdf Manifold models] | ||
* [http://redwood.berkeley.edu/vs265/adaptation-lecture.pdf (an aside on adaptation)] | * [http://redwood.berkeley.edu/vs265/adaptation-lecture.pdf (an aside on adaptation)] | ||
==== Nov 13 ==== | |||
* Attractor neural nets [http://redwood.berkeley.edu/vs265/attractor-lecture.pdf slides] | |||
==== Nov 18 ==== | |||
* Guy Isely [http://redwood.berkeley.edu/vs265/Guy-Isely-neurocomputation-rnns.pdf slides] | |||
* Brian Cheung [http://redwood.berkeley.edu/vs265/Brian-Cheung-LSTMS.pdf slides] | |||
* [https://archive.org/details/VS265-Fall14-Nov18 video] | |||
==== Nov 20 ==== | |||
* Probabilistic Models [http://redwood.berkeley.edu/vs265/prob-models-lecture.pdf slides] | |||
* [https://archive.org/details/VS265-Fall14-Nov20 video] | |||
==== Nov 25 ==== | |||
* Boltzmann machine [http://redwood.berkeley.edu/vs265/boltzmann-machine.pdf slides] | |||
* [https://archive.org/details/VS265-Fall14-Nov25 Nov 25] | |||
* [https://archive.org/details/VS265-Fall14-Dec2 Dec 2] | |||
==== Dec 4 ==== | |||
* [https://archive.org/details/VS265-Fall14-Dec4 ICA Talk by Tony Bell] | |||
==== Dec 9 ==== | |||
* Kalman filter [http://redwood.berkeley.edu/vs265/kalman-slides.pdf slides] | |||
* Spiking neurons [http://redwood.berkeley.edu/vs265/spikes-slides.pdf slides] | |||
* [https://archive.org/details/VS265-Fall14-Dec9 lecture video] | |||
* [http://redwood.berkeley.edu/w/images/9/92/Adelson.pdf tmp] | |||
* [[File:x.pdf]] | |||
Latest revision as of 20:59, 26 June 2015
28 Aug
4 Sept
- Neuron models, membrane equation video
11 Sept
- Paul Rhodes guest lecture video
16 Sept
- Perceptron model video
18 Sept
- Supervised learning
- Neural Networks Followup video
23,25 Sept
Sep 30, Oct 2
Oct 7
Oct 9
Oct 14
Oct 16
Oct 21,23,28
- Sparse coding slides
- Oct23rd video
- Oct28th video
Oct 30, Nov. 4, 6
- Oct30 Video
- Nov4 Video
- Nov6 Video
- Nov 13 Video
- Self-organizing maps
- Manifold models
- (an aside on adaptation)
Nov 13
- Attractor neural nets slides
Nov 18
Nov 20
Nov 25
Dec 4
Dec 9
- Kalman filter slides
- Spiking neurons slides
- lecture video
- tmp
- File:X.pdf
