VS298: Natural Scene Statistics: Difference between revisions
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| Feb. 3 | | Feb. 3 | ||
| Barlow: Theory of redundancy reduction [https://www.dropbox.com/s/y7qgngopjrf5pvs/barlow61.pdf paper] <br /> | | ''Redundancy reduction, whitening, and power spectrum of natural images'' | ||
Barlow: Theory of redundancy reduction [https://www.dropbox.com/s/y7qgngopjrf5pvs/barlow61.pdf paper] <br /> | |||
Atick: Theory of whitening [http://redwood.berkeley.edu/bruno/nss/atick-redlich92.pdf paper] <br /> | Atick: Theory of whitening [http://redwood.berkeley.edu/bruno/nss/atick-redlich92.pdf paper] <br /> | ||
Field: 1/f<sup>2</sup> power spectrum and sparse coding [http://redwood.berkeley.edu/bruno/nss/field87.pdf paper] | Field: 1/f<sup>2</sup> power spectrum and sparse coding [http://redwood.berkeley.edu/bruno/nss/field87.pdf paper] | ||
| Anthony DiFranco<br /> | | <br /> | ||
Anthony DiFranco<br /> | |||
Dylan Paiton<br /> | Dylan Paiton<br /> | ||
Michael Levy | Michael Levy | ||
Revision as of 00:12, 29 January 2014
This seminar will examine what is known about the statistical structure of natural visual and auditory scenes, and theories of how sensory coding strategies have been adapted to this structure. Topics include:
- Theories of efficient and robust coding
- ICA and sparse coding
- Energy-based models: 'Product of experts' and 'Fields of experts'
- Learning invariant representations through ‘slow feature analysis’
- Manifold and Lie group models
- Hierarchical models and ‘deep networks’
Instructor: Bruno Olshausen
Enrollment information:
VS 298 (section 4), 2 units
CCN: 66489
Meeting time and place:
Monday 6-8, Evans 560
Schedule:
| Date | Topic/Reading | Presenter |
|---|---|---|
| Feb. 3 | Redundancy reduction, whitening, and power spectrum of natural images
Barlow: Theory of redundancy reduction paper |
Anthony DiFranco |
| Feb. 10 | ||
| Feb. 17 | ** Holiday ** | |
| Feb. 24 | ||
| March 3 | ||
| March 10 | ||
| March 17 | ||
| March 24 | ||
| March 31 | ** Spring recess ** | |
| April 7 | ||
| April 14 | ||
| April 21 | ||
| April 28 | ||
| May 5 | ||
| May 12 |
