Difference between revisions of "VS298: Natural Scene Statistics"

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! Topic/Reading
 
! Topic/Reading
 
! Presenter
 
! Presenter
|-
+
|- valign="top"
 
| Feb. 3
 
| Feb. 3
 
| '''Redundancy reduction, whitening, and power spectrum of natural images'''
 
| '''Redundancy reduction, whitening, and power spectrum of natural images'''
Line 39: Line 39:
 
* Field (1987):  1/f<sup>2</sup> power spectrum and sparse coding [https://www.dropbox.com/s/jenlrgxxvm4h539/field87.pdf paper]
 
* Field (1987):  1/f<sup>2</sup> power spectrum and sparse coding [https://www.dropbox.com/s/jenlrgxxvm4h539/field87.pdf paper]
 
Additional reading:
 
Additional reading:
* Attneave
+
* Attneave (1954) - 'Some informational aspects of visual perception' [https://www.dropbox.com/s/z57af14zjomnuxe/attneave54.pdf paper]
* Laughlin
+
* Laughlin (1981) - Histogram equalization of contrast response [https://www.dropbox.com/s/lhdd9dpz22nqa73/laughlin81.pdf paper]
* Srinivasan
+
* Srinivasan (1982) - 'Predictive coding: a fresh view of inhibition in the retina' [https://www.dropbox.com/s/rkvl45yiapf4jfz/srinivasan-etal82.pdf paper]
* Switkes
+
* Switkes (1978) - Power spectrum of carpentered environments [https://www.dropbox.com/s/d14ktt9kgjimlx6/switkes-carpentered.pdf paper]
* Ruderman
+
* Ruderman (1997) - Why are images 1/f<sup>2</sup>? [https://www.dropbox.com/s/clbwm63gkn036xq/ruderman-scaling.pdf paper]
* Torralba
+
* Torralba & Oliva (2003) - Power spectrum of natural image categories [https://www.dropbox.com/s/ybgzoc6egw99wee/torralba-oliva03.pdf paper]
| valign="top"
+
|<br />
<br />
 
 
Anthony DiFranco<br />
 
Anthony DiFranco<br />
 
Dylan Paiton<br />
 
Dylan Paiton<br />
 
Michael Levy
 
Michael Levy
|-
+
|- valign="top"
 
| Feb. 10
 
| Feb. 10
 
|  '''Whitening in time and color; Robust coding''' <br />
 
|  '''Whitening in time and color; Robust coding''' <br />
* Dong & Atick (1995):  spatiotemporal power spectrum of natural movies [https://www.dropbox.com/s/npqsum1jx35so8p/dong-atick95.pdf paper] <br />
+
* Dong & Atick (1995):  spatiotemporal power spectrum of natural movies [https://www.dropbox.com/s/npqsum1jx35so8p/dong-atick95.pdf paper]  
* Ruderman (1998):  statistics of cone responses [https://www.dropbox.com/s/qpo6v0viush5k0o/ruderman-color.pdf paper] <br />
+
* Ruderman (1998):  statistics of cone responses [https://www.dropbox.com/s/qpo6v0viush5k0o/ruderman-color.pdf paper]  
 
* Karklin & Simoncelli (2012):  noisy population coding of natural images [https://www.dropbox.com/s/m4wc2c2v9p0vqyu/karklin-simoncelli12.pdf paper]
 
* Karklin & Simoncelli (2012):  noisy population coding of natural images [https://www.dropbox.com/s/m4wc2c2v9p0vqyu/karklin-simoncelli12.pdf paper]
 +
Additional reading:
 +
* Dong & Atick (1995) - spatiotemporal decorrelation using lagged and non-lagged cells  [https://www.dropbox.com/s/lt13hc4mgcre5j3/dong-atick-decorrelation.pdf paper]
 +
* Doi & Lewicki (2007) - A theory of retinal population coding [https://www.dropbox.com/s/kz0jfeiblcpha1e/doi-lewicki07.pdf paper]
 
| <br />
 
| <br />
 
Chayut Thanapirom<br />
 
Chayut Thanapirom<br />
Line 64: Line 66:
 
|  ** Holiday **
 
|  ** Holiday **
 
|  
 
|  
|-
+
|- valign="top"
 
| Feb. 24
 
| Feb. 24
 
|  '''Higher-order statistics and sensory coding''' <br />
 
|  '''Higher-order statistics and sensory coding''' <br />
* Barlow (1972): Sparse coding <br />
+
* Barlow (1972): Sparse coding [https://www.dropbox.com/s/iqm62gnmje61y5c/barlow72.pdf paper]<br />
* Field (1994): What is the goal of sensory coding? <br />
+
* Field (1994): What is the goal of sensory coding? [https://www.dropbox.com/s/ufvvznv0xx48ncf/field94.pdf paper]<br />
* Bell & Sejnowski (1996):  Independent components analysis.
+
* Bell & Sejnowski (1995):  Independent component analysis. [https://www.dropbox.com/s/qre5l2y1i6p5rlp/bell-sejnowski95.pdf paper]<br />
|  
+
Additional reading:
|-
+
* Redlich (1993):  Redundancy Reduction as a Strategy for Unsupervised Learning.  [https://www.dropbox.com/s/f9kp7pwh9g4n0xx/redlich93.pdf paper]
 +
* Baddeley (1996): Searching for filter with 'interesting' output distributions: An uninteresting direction to explore?  [https://www.dropbox.com/s/cioqfzgadb1fd5l/baddeley96.pdf paper]
 +
* O'regan & Noe (2001): A sensorimotor account of vision and visual consciousness  [https://www.dropbox.com/s/9yg4je9wb1lohuq/oregan-noe01.pdf paper]
 +
| <br />
 +
Karl Zipser <br />
 +
Michael Levy<br />
 +
Mayur Mudigonda
 +
|- valign="top"
 
| March 3
 
| March 3
|  '''ICA and sparse coding''' <br />
+
|  '''ICA and sparse coding of natural images''' <br />
* Bell & Sejnowski (1997): ICA of natural images <br/>
+
* Bell & Sejnowski (1997): ICA of natural images [https://www.dropbox.com/s/n2y1fqf9zix5wfc/bell-sejnowski97.pdf paper]<br/>
* Olshausen & Field (1997):  Sparse coding of natural images <br />
+
* Olshausen & Field (1997):  Sparse coding of natural images [https://www.dropbox.com/s/np4kiyo2yfqtyuq/olshausen-field97.pdf paper]<br />
* van Hateren & Ruderman (1998), Olshausen (2003):  ICA/sparse coding of natural video
+
* van Hateren & Ruderman (1998), Olshausen (2003):  ICA/sparse coding of natural video [https://www.dropbox.com/s/jucelyqdkde23g9/olshausen-video03.pdf paper1], [https://www.dropbox.com/s/f3mxyw1sw0devb4/vanhateren-ruderman98.pdf paper2] <br />
|  
+
Additional reading:
|-
+
* Olshausen & Field (1996): simpler explanation of sparse coding [https://www.dropbox.com/s/wridvqn9fqalnn5/olshausen-field96.pdf paper]
| March 10
+
| <br />
 +
Mayur Mudigonda<br />
 +
Zayd Enam<br />
 +
Georgios Exarchakis
 +
|-  
 +
| March 11 **Tuesday**
 
|  '''Statistics of natural sound and auditory coding''' <br />
 
|  '''Statistics of natural sound and auditory coding''' <br />
* Clark & Voss: '1/f noise and music' <br />
+
* Clark & Voss: '1/f noise and music' [https://www.dropbox.com/s/mfidr4wfsuppgp3/voss-clarke78.pdf paper]<br />
* Smith & Lewicki: sparse coding of natural sound <br />
+
* Smith & Lewicki: sparse coding of natural sound [https://www.dropbox.com/s/o4so96di3fdkzu4/smith-lewick06.pdf paper]<br />
* Klein/Deweese:  ICA/sparse coding of spectrograms  
+
* Klein/Deweese:  ICA/sparse coding of spectrograms [https://www.dropbox.com/s/6txhh3y3xapvvci/klein-kording03.pdf paper1], [https://www.dropbox.com/s/damynt0ruugy1v3/carlson-deweese12.pdf paper2]
 
| <br />
 
| <br />
 
Tyler Lee<br />
 
Tyler Lee<br />
TBD<br />
+
Yubei Chen<br />
 
TBD
 
TBD
|-
+
|- valign="top"
 
| March 17
 
| March 17
 
|  '''Higher-order group structure''' <br />
 
|  '''Higher-order group structure''' <br />
* Geisler: contour statistics <br />
+
* Geisler: contour statistics [https://www.dropbox.com/s/2167nccf3pbhl48/geisler-etal01.pdf paper] <br />
* Hyvarinen:  subspace ICA/topgraphic ICA <br />
+
* Hyvarinen:  subspace ICA/topgraphic ICA [https://www.dropbox.com/s/322pakrrau9vl5g/hyvarinen2000.pdf paper1], [https://www.dropbox.com/s/zigl3gzursjmod1/hyvarinen-hoyer01.pdf paper2]<br />
* Lyu & Simoncelli: radial Gaussianization
+
* Lyu & Simoncelli: radial Gaussianization [https://www.dropbox.com/s/j87vewntbg1rzdl/lyu-simoncelli09.pdf paper]<br />
 +
Additional reading:
 +
* Parent & Zucker (1989): Trace Inference, Curvature Consistency, and Curve Detection, [https://www.dropbox.com/s/9a56qnpgaq7h60n/parent-zucker89.pdf paper]<br />
 +
* Field et al. (1993): Contour Integration by the Human Visual System: Evidence for a Local “Association Field” [https://www.dropbox.com/s/qgcsvzk2i2is5d0/field-etal93.pdf paper]<br />
 +
* Zetzsche et al. (1999): The atoms of vision: Cartesian or polar? [https://www.dropbox.com/s/78th56ytm8rayjs/zetzsche-etal99.pdf paper]<br />
 +
* Garrigues & Olshausen (2010): Group Sparse Coding with a Laplacian Scale Mixture Prior, [https://www.dropbox.com/s/mgfg0rt7q9tokbz/garrigues-olshausen10.pdf paper]
 
| <br />
 
| <br />
TBD<br />
+
Chayut Thanapirom<br />
 
Guy Isely<br />
 
Guy Isely<br />
 
TBD
 
TBD
Line 102: Line 121:
 
|  ** Spring recess **
 
|  ** Spring recess **
 
|  
 
|  
|-
+
|- valign="top"
 
| March 31
 
| March 31
 
|  '''Energy-based models''' <br />
 
|  '''Energy-based models''' <br />
* Hinton:  Restricted Boltzmann machine <br />
+
* Hinton:  Product of experts models, [https://www.dropbox.com/s/iow62b9nqbbxftw/hinton-poe-nc02.pdf paper] <br />
* Osindero & Hinton:  Product of Experts <br />
+
* Osindero & Hinton:  Product of Experts model of natural images, [https://www.dropbox.com/s/rkl97yw1ryvosya/osindero-welling-hinton06.pdf paper]<br />
* Roth & Black:  Fields of experts
+
* Roth & Black:  Fields of experts, [https://www.dropbox.com/s/w6lhf9li8tsexnm/roth-black05.pdf paper] <br />
|  
+
Additional reading:
 +
* Hinton:  Practical guide to training RBMs [https://www.dropbox.com/s/8kxbkrmay5h9abf/hinton-rbm-guideTR.pdf paper] <br />
 +
* Teh et al:  Energy-based models for sparse overcomplete representation, [https://www.dropbox.com/s/ph17gczh2l1e9qa/teh-etal-jmlr03.pdf paper]<br />
 +
* Zhu, Wu & Mumford:  FRAME (Filters, random fields, and maximum entropy), [https://www.dropbox.com/s/fxcc1gx1vfz1mwo/zhu-wu-mumford-FRAME.pdf paper]
 +
| <br />
 +
Evan Shelhamer<br />
 +
Brian Cheung<br />
 +
Chris Warner
 
|-
 
|-
 
| April 7
 
| April 7
 
|  '''Learning invariances through 'slow feature analysis'''' <br />
 
|  '''Learning invariances through 'slow feature analysis'''' <br />
* Foldiak/Wiskott: slow feature analysis <br />
+
* Foldiak/Wiskott: slow feature analysis, [https://www.dropbox.com/s/ce4ngfyop94whhj/foldiak91.pdf paper1], [https://www.dropbox.com/s/v3dgj50jp6sc26p/wiskott-sejnowski02.pdf paper2]<br />
* Hyvarinen:  'Bubbles' <br />
+
* Hyvarinen:  'Bubbles' [https://www.dropbox.com/s/1u7cmflubvt0zfy/hyvarinen-bubbles03.pdf paper]<br />
* Berkes et al.:  factorizing 'what' and 'where' from video
+
* Berkes et al.:  factorizing 'what' and 'where' from video, [https://www.dropbox.com/s/us4fmd6vphacc4x/berkes-etal09.pdf paper]
|  
+
| <br />
 +
Guy Isely<br />
 +
Chayut Thanapirom<br />
 +
Bharath Hariharan
 
|-
 
|-
 
| April 14
 
| April 14
 
|  '''Manifold and Lie group models''' <br />
 
|  '''Manifold and Lie group models''' <br />
* Carlsson:  Klein bottle model of natural images
+
* Carlsson et al.:  Klein bottle model of natural images, [https://www.dropbox.com/s/egaeuqpr7spuaaq/carlsson-etal07.pdf paper]
* Culpepper & Olshausen: Learning manifold transport operators
+
* Culpepper & Olshausen: Learning manifold transport operators, [https://www.dropbox.com/s/1yqnpg7mfodfd8y/culpepper-olshausen09.pdf paper]
* Roweis & Saul: Local Linear Embedding
+
* Roweis & Saul: Local Linear Embedding,  [https://www.dropbox.com/s/xbslejj4jl7723q/roweis-saul00.pdf paper]
|  
+
| <br />
 +
Yubei Chen<br />
 +
Bruno/Mayur<br />
 +
James Arnemann
 
|-
 
|-
 
| April 21
 
| April 21
 
| '''Hierarchical models''' <br />
 
| '''Hierarchical models''' <br />
* Karklin & Lewicki (2003):  density components <br />
+
* Karklin & Lewicki (2003):  density components, [https://www.dropbox.com/s/urjwi875vhtmyww/karklin-lewicki03.pdf paper] <br />
* Shan & Cottrell:  stacked ICA <br />
+
* Shan & Cottrell:  stacked ICA, [https://www.dropbox.com/s/vit1tyjsz75jalf/shan-cottrell07.pdf paper] <br />
* Cadieu & Olshausen (2012):  learning intermediate representations of form and motion
+
* Cadieu & Olshausen (2012):  learning intermediate representations of form and motion, [https://www.dropbox.com/s/p0bsnjxq3v6rs0x/cadieu-olshausen12.pdf paper]
|  
+
| <br />
 +
Tyler Lee<br />
 +
Brian Cheung<br />
 +
Dylan Paiton
 
|-
 
|-
 
| April 28
 
| April 28
 
|  '''Deep network models''' <br />
 
|  '''Deep network models''' <br />
* Hinton & Salakhudinov (2006):  stacked RBMs <br />
+
* Hinton & Salakhudinov (2006):  stacked RBMs, [https://www.dropbox.com/s/bjtfiiu44skwuzl/hinton-salakutdinov06.pdf paper] <br />
* Le et al. (2011):  Google brain <br />
+
* Le et al. (2011):  Unsupervised learning (Google brain, 'cat' neurons), [https://www.dropbox.com/s/ydd91bhv0qj69rr/le-etal12.pdf paper] <br />
* Krishevsky et al. (2012)/Fergus (2013):  visualizing deep nets
+
* Krishevsky et al. (2012): Supervised learning, ImageNet 1000 [http://books.nips.cc/papers/files/nips25/NIPS2012_0534.pdf paper]
|  
+
| <br />
 +
TBD <br />
 +
TBD <br />
 +
[mailto:abbasi@berkeley.edu Reza Abbasi-Asl]
 
|-
 
|-
| May 5
+
| May 6 <br />
 +
Note: Tuesday
 
|  '''Special topics''' <br />
 
|  '''Special topics''' <br />
 
+
* Fergus (2013):  visualizing what deep nets learn [http://arxiv.org/abs/1311.2901 paper]<br />
|  
+
* Schmidhuber:  deep nets ([http://arxiv.org/pdf/1312.5548.pdf paper]), focusing on LOCOCODE ([http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.51.1412 paper])
 +
* Image compression with Hopfield networks <br />
 +
| <br />
 +
[mailto:shiry@berkeley.edu Shiry Ginosar]<br />
 +
Anthony DiFranco<br />
 +
Chris Hillar
 
|-
 
|-
 
| May 12
 
| May 12

Latest revision as of 20:27, 25 May 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.


Instructor: Bruno Olshausen

Enrollment information:

VS 298 (section 4), 2 units
CCN: 66489

Meeting time and place:

Monday 6-8, Evans 560

Email list:

nss2014@lists.berkeley.edu subscribe


Readings:

Books and review articles:

  • Natural Image Statistics by Hyvarinen, Hurri & Hoyer
  • Olshausen BA & Lewicki MS (2013) What natural scene statistics can tell us about cortical representation. In: The Cognitive Neurosciences V. paper
  • Geisler WS (2008) Visual perception and the statistical properties of natural scenes. Annual Review of Psychology paper

Weekly 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

Additional reading:

  • Attneave (1954) - 'Some informational aspects of visual perception' paper
  • Laughlin (1981) - Histogram equalization of contrast response paper
  • Srinivasan (1982) - 'Predictive coding: a fresh view of inhibition in the retina' paper
  • Switkes (1978) - Power spectrum of carpentered environments paper
  • Ruderman (1997) - Why are images 1/f2? paper
  • Torralba & Oliva (2003) - Power spectrum of natural image categories 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

Additional reading:

  • Dong & Atick (1995) - spatiotemporal decorrelation using lagged and non-lagged cells paper
  • Doi & Lewicki (2007) - A theory of retinal population coding paper

Chayut Thanapirom
Michael Levy
Yubei Chen

Feb. 17 ** Holiday **
Feb. 24 Higher-order statistics and sensory coding
  • Barlow (1972): Sparse coding paper
  • Field (1994): What is the goal of sensory coding? paper
  • Bell & Sejnowski (1995): Independent component analysis. paper

Additional reading:

  • Redlich (1993): Redundancy Reduction as a Strategy for Unsupervised Learning. paper
  • Baddeley (1996): Searching for filter with 'interesting' output distributions: An uninteresting direction to explore? paper
  • O'regan & Noe (2001): A sensorimotor account of vision and visual consciousness paper

Karl Zipser
Michael Levy
Mayur Mudigonda

March 3 ICA and sparse coding of natural images
  • Bell & Sejnowski (1997): ICA of natural images paper
  • Olshausen & Field (1997): Sparse coding of natural images paper
  • van Hateren & Ruderman (1998), Olshausen (2003): ICA/sparse coding of natural video paper1, paper2

Additional reading:

  • Olshausen & Field (1996): simpler explanation of sparse coding paper

Mayur Mudigonda
Zayd Enam
Georgios Exarchakis

March 11 **Tuesday** Statistics of natural sound and auditory coding
  • Clark & Voss: '1/f noise and music' paper
  • Smith & Lewicki: sparse coding of natural sound paper
  • Klein/Deweese: ICA/sparse coding of spectrograms paper1, paper2

Tyler Lee
Yubei Chen
TBD

March 17 Higher-order group structure
  • Geisler: contour statistics paper
  • Hyvarinen: subspace ICA/topgraphic ICA paper1, paper2
  • Lyu & Simoncelli: radial Gaussianization paper

Additional reading:

  • Parent & Zucker (1989): Trace Inference, Curvature Consistency, and Curve Detection, paper
  • Field et al. (1993): Contour Integration by the Human Visual System: Evidence for a Local “Association Field” paper
  • Zetzsche et al. (1999): The atoms of vision: Cartesian or polar? paper
  • Garrigues & Olshausen (2010): Group Sparse Coding with a Laplacian Scale Mixture Prior, paper

Chayut Thanapirom
Guy Isely
TBD

March 24 ** Spring recess **
March 31 Energy-based models
  • Hinton: Product of experts models, paper
  • Osindero & Hinton: Product of Experts model of natural images, paper
  • Roth & Black: Fields of experts, paper

Additional reading:

  • Hinton: Practical guide to training RBMs paper
  • Teh et al: Energy-based models for sparse overcomplete representation, paper
  • Zhu, Wu & Mumford: FRAME (Filters, random fields, and maximum entropy), paper

Evan Shelhamer
Brian Cheung
Chris Warner

April 7 Learning invariances through 'slow feature analysis'
  • Foldiak/Wiskott: slow feature analysis, paper1, paper2
  • Hyvarinen: 'Bubbles' paper
  • Berkes et al.: factorizing 'what' and 'where' from video, paper

Guy Isely
Chayut Thanapirom
Bharath Hariharan

April 14 Manifold and Lie group models
  • Carlsson et al.: Klein bottle model of natural images, paper
  • Culpepper & Olshausen: Learning manifold transport operators, paper
  • Roweis & Saul: Local Linear Embedding, paper

Yubei Chen
Bruno/Mayur
James Arnemann

April 21 Hierarchical models
  • Karklin & Lewicki (2003): density components, paper
  • Shan & Cottrell: stacked ICA, paper
  • Cadieu & Olshausen (2012): learning intermediate representations of form and motion, paper

Tyler Lee
Brian Cheung
Dylan Paiton

April 28 Deep network models
  • Hinton & Salakhudinov (2006): stacked RBMs, paper
  • Le et al. (2011): Unsupervised learning (Google brain, 'cat' neurons), paper
  • Krishevsky et al. (2012): Supervised learning, ImageNet 1000 paper

TBD
TBD
Reza Abbasi-Asl

May 6

Note: Tuesday

Special topics
  • Fergus (2013): visualizing what deep nets learn paper
  • Schmidhuber: deep nets (paper), focusing on LOCOCODE (paper)
  • Image compression with Hopfield networks

Shiry Ginosar
Anthony DiFranco
Chris Hillar

May 12 Special topics