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.
Instructor: Bruno Olshausen
Enrollment information:
VS 298 (section 4), 2 units
CCN: 66489
Meeting time and place:
Monday 6-8, Evans 560
General reading:
- Natural Image Statistics by Hyvarinen, Hurri & Hoyer
- Geisler WS (2008) Visual perception and the statistical properties of natural scenes. Annual Review of Psychology paper
Schedule:
Date
|
Topic/Reading
|
Presenter
|
Feb. 3
|
Redundancy reduction, whitening, and power spectrum of natural images
- Barlow (1961): Theory of redundancy reduction paper
- Atick (1992): Theory of whitening paper
- Field (1987): 1/f2 power spectrum and sparse coding paper
|
Anthony DiFranco
Dylan Paiton
Michael Levy
|
Feb. 10
|
Whitening in time and color; Robust coding
- Dong & Atick (1995): spatiotemporal power spectrum of natural movies paper
- Ruderman (1998): statistics of cone responses paper
- Karklin & Simoncelli (2012): noisy population coding of natural images paper
|
|
Feb. 17
|
** Holiday **
|
|
Feb. 24
|
Higher-order statistics and sensory coding
- Barlow (1972): Sparse coding
- Field (1994): What is the goal of sensory coding?
- Bell & Sejnowski (1996): Independent components analysis.
|
|
March 3
|
ICA and sparse coding
- Bell & Sejnowski (1997): ICA of natural images
- Olshausen & Field (1997): Sparse coding of natural images
- van Hateren & Ruderman (1998), Olshausen (2003): ICA/sparse coding of natural video
|
|
March 10
|
Statistics of natural sound and auditory coding
- Clark & Voss: '1/f noise and music'
- Smith & Lewicki: sparse coding of natural sound
- Klein/Deweese: ICA/sparse coding of spectrograms
|
|
March 17
|
Higher-order group structure
- Geisler: contour statistics
- Hyvarinen: subspace ICA/topgraphic ICA
- Lyu & Simoncelli: radial Gaussianization
|
|
March 24
|
** Spring recess **
|
|
March 31
|
Energy-based models
- Hinton: Restricted Boltzmann machine
- Osindero & Hinton: Product of Experts
- Roth & Black: Fields of experts
|
|
April 7
|
Learning invariances through 'slow feature analysis'
- Foldiak/Wiskott: slow feature analysis
- Hyvarinen: 'Bubbles'
- Berkes et al.: factorizing 'what' and 'where' from video
|
|
April 14
|
Manifold and Lie group models
- Carlsson: Klein bottle
- Culpepper & Olshausen: Learning manifold transport operators
- Roweis & Saul: Local Linear Embedding
|
|
April 21
|
Hierarchical models
- Karklin & Lewicki (2003): density components
- Shan & Cottrell: stacked ICA
- Cadieu & Olshausen (2012): learning intermediate representations of form and motion
|
|
April 28
|
Deep network models
- Hinton & Salakhudinov (2006): stacked RBMs
- Le et al. (2011): Google brain
- Krishevsky et al. (2012)/Fergus (2013): visualizing deep nets
|
|
May 5
|
Special topics
|
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May 12
|
Special topics
|
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