Curriculum Vitae

Bruno A. Olshausen

Born September 28, 1962, Sunset Beach, California.

Address: 2403 McGee Avenue [email protected] Berkeley, California 94703 http://redwood.berkeley.edu/bruno (530) 518-0859 (cell) (510) 642-7250 (office)

Degrees

Ph.D. 1994 Computation and Neural Systems, California Institute of Technology. M.S. 1987 Electrical Engineering, Stanford University. B.S. 1986 Electrical Engineering, Stanford University.

Positions

2010– Professor, Helen Wills Neuroscience Institute and School of Optometry, University of California, Berkeley. 2005– Director, Redwood Center for Theoretical Neuroscience, UC Berkeley. 2005–2010 Associate Professor, Helen Wills Neuroscience Institute and School of Op- tometry, University of California, Berkeley. 2003–2005 Associate Professor, Section of Neurobiology, Physiology & Behavior, Uni- versity of California, Davis. 2002–2005 Senior Research Scientist, Redwood Neuroscience Institute, Menlo Park, California. 2001–2003 Associate Professor, Department of Psychology, University of California, Davis. 1996–2001 Assistant Professor, Department of Psychology, University of California, Davis. 1996 Postdoctoral Fellow, Center for Biological and Computational Learning, Massachusetts Institute of Technology. 1994–1996 Postdoctoral Fellow, Department of Psychology, Cornell University. 1987–1989 Research Associate, Research Institute for Advanced Computer Science, NASA Ames Research Center. Awards and honors

2007– Fellow, Canadian Institute for Advanced Research, Learning in Brains and Machines program. 2008–2009 Fellow, Wissenschaftskolleg zu Berlin

Patents

2008 Rozell CJ, Olshausen BA, Baraniuk RG, Johnson DH, Ortman RL, “Ana- log System For Computing Sparse Codes,” U.S. Patent Application No: 12/035,424

Grants

Active 2019–2021 Bruno A. Olshausen, P.I., Pentti Kanerva, Co-P.I., “Computing in Holo- graphic Representation,” Air Force Office of Scientific Research, $412,000 (total) 2017–2020 Friedrich Sommer, P.I., Bruno A. Olshausen, Co-P.I., Saeed Saremi, Co- P.I., “RI: Small: Extracting and understanding sparse structure in spa- tiotemporal data,” NSF, $500,000 (total) 2016–2020 Bruno A. Olshausen, P.I., Sayeef Salahuddin, Lead-P.I., “ENIGMA: En- ergy Efficient Learning Machines using Hyper-Dimensional Vector Space Model,” NSF/SRC, $400,000 (total) Past 2012–2017 Bruno A. Olshausen, P.I., Naresh Shanbag, Lead-P.I., “Systems on Nanoscale Information Fabrics,” SRC Starnet, $960,000 (total) 2015–2016 Bruno A. Olshausen, P.I., “Perceptual Systems Based on Cortical Compu- tation,” DARPA, $591,416 (total) 2011–2016 Bruno A. Olshausen, P.I., Michael S. Lewicki, P.I., Wilson S. Geisler, P.I., “RI: Large: Collaborative Research: 3D structure and motion in dynamic natural scenes,” NSF (IIS-1111654), $680,000 (total) 2008–2016 Bruno A. Olshausen, P.I., Chris Rozell, co-P.I., “Unsupervised Learning of Hierarchical Structure in Multi-Band Imagery,” National Geospatial- Intelligence Agency (HM1582-08-1-0007), $298,480 (total). 2009–2015 Bruno A. Olshausen, P.I., Charles M. Gray, P.I., Christopher J. Rozell, P.I. “CRCNS: Neural Population Coding of Dynamic Natural Scenes, NIH (R01 EY019965), $1,726,284 (total) 2009–2014 Frederic Theunissen, P.I., Michael Gastpar, co-P.I., Bruno A. Olshausen, co-P.I. “CRCNS: Ethological Theories of Optimal Auditory Processing,” NIH (R01 DC007293), $1,000,000 (direct) 2009–2013 Kilian Koepsell, P.I., Bruno A. Olshausen, co-P.I., “RI:Multivariate Phase Models for Image and Signal Processing,” NSF, $442,888 (total) 2009–2011 Paul Rhodes, P.I., Stephen Baccus, Gert Cauwenberghs, Jim DiCarlo, Costa Colbert, Jack Gallant, Christopher Geyer, Tibor Kozek, Bruno Ol- shausen, co-P.I.s, “Neovision2,” DARPA. 2007–2011 Bruno A. Olshausen, P.I., David K. Warland, P.I., “Collaborative research: Hierarchical models of time-varying natural images,” NSF (IIS-0705939) $439,935 (total). 2007–2009 Friedrich T. Sommer, P.I., Bruno A. Olshausen, co-P.I., “CRCNS data sharing: Central facility and services,” NSF (IIS-0749049) $200,000 (total). 2006–2007 Bruno A. Olshausen, P.I., David K. Warland, co-P.I., “Collaborative re- search: Hierarchical models of time-varying natural images,” NSF (IIS- 0625223) $100,000 (total). 2005–2008 David K. Warland, P.I., Bruno A. Olshausen, Co-P.I., “Bilinear mod- els of natural images and their application to image analysis,” National Geospatial- Intelligence Agency, (HM1582-05-1-2017) $460,209 (total). 2002–2006 Bruno A. Olshausen, P.I., “Sensory coding and the natural environment,” NIH (R13-MH065347) $72,000 (direct). 2001–2005 Bruno A. Olshausen, P.I., “Informatics of human and monkey brain at- lases,” (Project 4 of Program project, Ted Jones, PI), NIH (P29-MH60975) $452,579 (direct). 2000–2005 Leo M. Chalupa, P.I., Bruno A. Olshausen, Co-PI, “Development and re- organization of prenatal visual system,” NEI (R01-EY03991) $1,250,000 (direct) 1999–2001 Charles M. Gray, P.I., Bruno A. Olshausen, Co-PI, “Neuronal Processing of Natural Images,” NEI (R01-EY12478) $570,000 (direct) 1998–2003 Bruno A. Olshausen, P.I., “Efficient Coding in Visual Cortex,” NIMH (R29-MH57921) $350,000 (direct)

Teaching

2005– School of Optometry, UC Berkeley

Neural Computation (VS 265), Graduate elective. An introduction to mathematical and computational models of the nervous system. Theories of learning and self- organization in neural systems; Generative models and inference; Recurrent net- works and dynamical systems. (15 weeks) Proseminar in Visual Neuroscience (VS 212B), Graduate core course. Neurobiological substrates of vision, from retina to cortex. (six 1.5-hour lectures)

Neuroanatomy/Neurophysiology of the Eye & Visual System (VS 206D), Clinical Op- tometry core course. Neural circuitry and information processing in the retina. (six two-hour lectures)

1996–2005 Dept. of Psychology and Dept. of Neurobiology, Physiology & Behavior, UC Davis Information Processing Models in Neuroscience and Psychology (NPB 163), Undergrad- uate/graduate elective. Mathematical tools as they are applied toward understand- ing information processing in nervous systems, including linear systems theory, Fourier transforms, neural networks, adaptive systems, probabilistic inference and information theory.

Sensory Processes (PSC 129), Undergraduate core course. Covers the neural mech- anisms underlying perception, the physics of light and sound, and psychological characterizations of perceptual processes.

Topics in Vision (NPB 261B), Graduate elective. Second quarter of three-quarter se- quence on vision, focuses on central mechanisms (LGN and cortex) drawing upon systems neuroscience, psychophysics, and computational modeling approaches.

Cognitive Neuroscience (PSC 263), Graduate core course. The neurobiological basis of higher mental function: visual and auditory cognition, attention, memory, lan- guage, and executive function.

Students

Current

Steven Shepard, Vision Science (second year)

Jasmine Collins, Computer Science (second year)

Vasha Dutell, Vision Science (fourth year)

Spencer Kent, Electrical Engineering (fourth year)

Shariq Mobin, Neuroscience (fourth year)

Sophia Sanborn, Psychology (fourth year)

Ryan Zarcone, Biophysics (fourth year)

Brian Cheung, Vision Science (sixth year) Dylan Paiton, Vision Science (sixth year)

Yubei Chen, Electrical Engineering (seventh year)

Eric Weiss, Neuroscience (seventh year)

Past

Alex Anderson, Ph.D. 2018, Physics, U.C. Berkeley. Thesis: “Noise, Quantization and Priors in Neural Networks.” (Currently at WaveOne)

Tyler Lee (co-advised with Frederic Theunissen), Ph.D. 2016, Neuroscience, U.C. Berke- ley. Thesis: “Hearing through the noise: biologically inspired noise reduction.” (Currently at Intel Nervana)

Chayut Thanapirom (co-advised with Mike DeWeese), Ph.D. 2016, Physics, U.C. Berke- ley. Thesis: “Neural Representation Learning with Denoising Autoencoder Frame- work.” (Currently at Google)

Zayd Enam, Bachelors honors thesis and Haas Fellow 2014, Electrical Engineering, U.C. Berkeley. Thesis: “Sparse multiscale representations for large images.” (Currently graduate student at Stanford, Electrical Engineering)

Michael Hadley, Masters 2013, Vision Science, U.C. Berkeley. Thesis: “Designing a Computational Foundation to Study Direction Selectivity: Starburst Amacrine Cells.” (Currently student at the School of the Art Institute of Chicago)

Jascha Sohl-Dickstein, Ph.D. 2012, Biophysics, U.C. Berkeley. Thesis: “Efficient Meth- ods for Unsupervised Learning of Probabilistic Models.” (Currently Senior Research Scientist at Google)

Amir Khosrowshahi, Ph.D. 2011, Vision Science, U.C. Berkeley. Thesis: “The lam- inar organization of V1 neural activity in response to dynamic natural scenes.” (Currently CTO and Co-founder, Nervana/Intel)

Jack Culpepper, Ph.D. 2011, Computer Science, U.C. Berkeley. Thesis: “Learned Fac- torization Models to Explain Variability in Natural Image Sequences.” (Currently at Yahoo labs)

Jimmy Wang, Ph.D. 2010, Vision Science, U.C. Berkeley. Thesis: “Learning Transfor- mations From Video.” (Currently at Zendar.io)

Charles Cadieu, Ph.D. 2009, Neuroscience, U.C. Berkeley. Thesis: “Probabilistic Mod- els of Phase Variables for Visual Representation and Neural Dynamics.” (Co- founder, Bay Labs)

Pierre Garrigues, Ph.D. 2009, Electrical Engineering, U.C. Berkeley. Thesis: “Sparse Coding Models of Natural Images: Algorithms for Efficient Inference and Learning of Higher-Order Structure.” (Currently group lead at Yahoo labs) Jeff Johnson, Ph.D. 2004. Neuroscience, U.C. Davis. Thesis: “Visual object recognition: Timing and occlusion-related effects.” (Currently Research staff at UC Davis)

Phil Sallee, Ph.D. 2004, Computer Science, U.C. Davis. Thesis: “Statistical methods for image and signal processing.” (Currently Senior Technical Staff at Raytheon)

Scott Murray, Ph.D. 2002, Neuroscience, U.C. Davis. Thesis: “Neural mechanisms of human shape perception.” (Currently Associate Professor, Dept. of Psychology, University of Washington)

Postdocs

Past

Jesse Engel, 2013-2014, Currently at Google labs.

Urs K¨oster,2009-2014, Currently at Cerebras.

Ian Stevenson, 2011-2013, Currently Assistant Professor, Dept. of Psychology, Univer- sity of Connecticut

Ivana Tosic, 2009-2011, Currently at Google labs.

Nicol Harper, 2008-2010, Currently Reearch scientist at University of Oxford.

Chris Rozell, 2007-2008, Currently Professor, Dept. of Electrical and Computer Engi- neering, Georgia Institute of Technology

Tim Blanche, 2006-2008, Currently Founder, White Matter, LLC.

Kilian Koepsell, 2005-2008 Currently Co-Founder, Bay Labs.

Matthias Bethge, 2003-2005, Currently Professor, Department of Physics, University of Tubingen, Germany

Jeff Colombe, 1999-2000, Currently Senior Scientist, The Mitre Corporation

Service

Editorial Board, The Journal of Computational Neuroscience.

Reviewer for Neural Computation, The Journal of Neuroscience, Network: Computa- tion in Neural Systems, Nature, Nature Neuroscience, Journal of Cognitive Neuro- science, The Journal of Computational Neuroscience, Neural Information Process- ing Systems, The National Science Foundation, The Wellcome Trust. UC Berkeley committees: Helen Wills Neuroscience Institute: Executive Committee (’05-present), Graduate Admissions (’06-’08; ’12-’13); School of Optometry: Fac- ulty Recruitment Committee (’12-’13), Admissions (’11-’13), Curriculum Commit- tee (’06-’07); Vision Science Program: Student Advisory Committee (’06-present), Curriculum Committee (’07-’08).

UC Davis committees: Dean’s Committee on Bioinformatics (’03-’04), Neuroscience Graduate Admissions (’01-’02), Computational Science Initiative (’00-’02), Mind Sciences Initiative (’99-’01), Dean’s Committee on Recruitment (’99-’00), Systems Neuroscience Search (’00-’01), Cognitive Neuroscience Search (’98-’01), Institute for Theoretical Dynamics Admissions (’98-’99), Developmental Psychobiology Search (’97-’98).

Workshops and Meetings organized

Simons Institute Program on Computation and the Brain, UC Berkeley, Spring semester 2018. (with Christos Papadimitriou, Sophie Deneve, Ila Fiete, Wofgang Maas, Bartlett Mel and Terry Sejnowski)

Kavli Futures Symposium on Theory of Neural Computation, Mathematical Sciences Research Institute, Berkeley, CA, October 3-5, 2015. (with Fritz Sommer, David Eisenbud, Christos Papadimitriou, Gary Marcus, Mitya Chklovskii, and Terry Se- jnowski)

Santa Fe Institute workshop on “Perception and Action,” Santa Fe, New Mexico, September 2010. (with Fritz Sommer, Jeff Hawkins and Murray Sherman)

Canadian Institute for Advanced Research workshop on “Natural Image Statistics and High Level Vision,” Berkeley, California, May 2008.

Cosyne workshop on “Requirements of a Visual Theory,” The Canyons, Park City, Utah, February 25, 2007. (with David Arathorn and Jim DiCarlo)

Redwood Center for Theoretical Neuroscience Inaugural Symposium, UC Berkeley, Oc- tober 7, 2005.

Cosyne workshop on “Visual Invariance,” Snowbird, Utah, February 2005. (with Dileep George)

Mathematical Sciences Research Institute workshop on “Neurobiological Vision,” Berke- ley, CA, February 7-11, 2005. (with David Donoho)

Gordon Research Conference on “Sensory Coding and the Natural Environment,” Ox- ford, UK, Sept. 5-10, 2004. (with Jack Gallant and Mike Lewicki)

American Institute of Mathematics workhop on “Inference and Prediction in Neocortical Circuits,” Palo Alto, CA, Sept. 21-24, 2003. (with Jeff Hawkins) Gordon Research Conference on “Sensory coding and the Natural Environment: Proba- bilistic Models of Perception,” Mount Holyoke College, MA, July 2002. (with Pam Reinagel)

Neural Information Processing Systems workshop on “Statistical Theories of Corti- cal Function,” Breckenridge, Colorado, December 1998. (with Raj Rao and Mike Lewicki)

“Natural Scene Statistics,” Hancock, Massachusetts, September 1997. (with Pam Reinagel, Dan Ruderman, and David Field).

Neural Information Processing Systems workshop on “Structure of Natural Images and Efficient Coding,” Snowmass, Colorado, December 1996. (with Dan Ruderman, USC)

Computation and Neural Systems workshop on “Statistics of Natural Images,” , Cam- bridge, Massachusetts, July 1996.

Neural Information Processing Systems workshop on “Selective Visual Attention,” Vail, Colorado, December 1993. (with Ernst Niebur, Caltech)

Computation and Neural Systems workshop on “Visual Attention,” Point Reyes, Cali- fornia, July 1992. (with Ernst Niebur and Marius Usher, Caltech)

Publications

Book:

Rao RPN, Olshausen BA, Lewicki M, Eds. (2002). Probabilistic Models of Perception and Brain Function. MIT Press.

Refereed papers: Anderson AG, Ratnam K, Roorda A, Olshausen BA (2019) High-Acuity Vision from Retinal Image Motion. (Submitted)

Zheng X, Zarcone R, Paiton D, Sohn J, Wan W, Olshausen BA, Wong HSP (2018) Error-Resilient Analog Image Storage and Compression with Analog-Valued RRAM Arrays: An Adaptive Joint Source-Channel Coding Approach. In 2018 IEEE In- ternational Electron Devices Meeting (IEDM).

Chen Y, Paiton DM, Olshausen BA (2018) The Sparse Manifold Transform. Neural Information Processing Systems, 31.

Engel JH, Eryilmaz SB, Kim S, BrightSky M, Lam C, Lung HL, Olshausen BA, Wong HS (2018) Opportunities for Analog Coding in Emerging Memory Devices. Nature Communications. (under review) Zarcone R, Paiton D, Anderson AG, Engel JH, Wong HS, Olshausen BA (2018) Joint Source-Channel Coding with Neural Networks for Analog Data Compression and Storage. Data Compression Conference (DCC) Proceedings.

Rahimi A, Datta S, Kleyko D, Frady P, Kanerva P, Olshausen BA, Rabaey J (2017) High-dimensional Computing as a Nanoscalable Paradigm. IEEE Transactions on Circuits and Systems, 64, 2508 - 2521.

Cheung B, Weiss E, Olshausen BA (2017) Emergence of foveal image sampling from learning to attend in visual scenes. International Conference on Learning Repre- sentations (ICLR) proceedings.

Engel JH, Eryilmaz SB, SangBum Kim, BrightSky, M, Chung Lam, Hsiang-Lan Lung, Olshausen BA, Wong H-SP (2014) Capacity optimization of emerging memory systems: A Shannon-inspired approach to device characterization. Electron Devices Meeting (IEDM), 2014 IEEE International, pp.29.4.1,29.4.4, 15-17 Dec. 2014

K¨osterU, Sohl-Dickstein J, Gray CM, Olshausen BA (2014) Modeling higher-order correlations within cortical microcolumns. PLOS Computational Biology, 10(7): e1003684. doi:10.1371/journal.pcbi.1003684

Lewicki MS, Olshausen BA, Surlykke A, Moss CF (2014) Scene analysis in the natural environment. Frontiers in Psychology, 5, article 199.

Cadieu CF, Olshausen BA (2012) Learning intermediate-level representations of form and motion from natural movies. Neural Computation, 24(4):827-66

Culpepper BJ, Sohl-Dickstein J, Olshausen BA (2011) Building a better probabilistic model of images by factorization. IEEE International Conference on Computer Vision. 6-13 Nov. 2011. pp. 2011-2017.

Tosic I, Olshausen BA, Culpepper BJ (2011) Learning sparse representations of depth. IEEE Journal of Selected Topics in Signal Processing, 5, 941-952.

Charles AS, Olshausen BA, Rozell CJ (2011) Learning sparse codes for hyperspectral imagery. IEEE Journal of Selected Topics in Signal Processing, 5, 963 - 978.

Wang CM, Sohl-Dickstein J, Tosic I, Olshausen BA (2011) Lie Group Transformation Models for Predictive Video Coding. In: Data Compression Conference 2011 pro- ceedings.

Garrigues PJ, Olshausen BA (2011) Group sparse coding with a Laplacian scale mixture prior. In: Advances in Neural Information Processing Systems, 23, J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, A. Culotta, Eds.

Culpepper BJ, Olshausen BA (2010) Learning transport operators for image manifolds. In: Advances in Neural Information Processing Systems, 22, Y. Bengio, D. Schu- urmans, J. Lafferty, C. K. I. Williams, A. Culotta, Eds. Cadieu CF, Olshausen BA (2009) Learning transformational invariants from time- varying natural images. In: Advances in Neural Information Processing Systems, 21, D. Koller, Y. Bengio, D. Schuurmans, L. Bottou, A. Culotta, Eds., Curran Associates. pp. 209-216.

Rozell CJ, Johnson DH, Baraniuk RG, Olshausen BA (2008) Sparse coding via thresh- olding and local competition in neural circuits. Neural Computation, 20, 2526-2563.

Garrigues P, Olshausen BA (2008) Learning horizontal connections in a sparse coding model of natural images. In: Advances in Neural Information Processing Systems, 20, J.C. Platt, D. Koller, Y. Singer, S. Roweis, Eds., Curran Associates. pp. 505– 512.

Johnson JS, Olshausen BA (2005) The recognition of partially visible natural objects in the presence and absence of their occluders. Vision Research, 45, 3262-3276.

Olshausen BA, Field DJ (2005) How close are we to understanding V1? Neural Com- putation, 17, 1665-1699.

Johnson JS, Olshausen BA (2005) The earliest EEG signatures of object recognition in a cued-target task are postsensory. Journal of Vision, 5, 299-312.

Barlow HB, Olshausen BA (2004) Convergent evidence for the visual analysis of optic flow through anisotropic attenuation of high spatial frequencies. Journal of Vision, 4, 415-426.

Johnson JS, Olshausen BA (2003) Timecourse of neural signatures of object recognition. Journal of Vision, 3, 499-512.

Sallee P, Olshausen BA (2003). Learning sparse multiscale image representations. In: Advances in Neural Information Processing Systems, 15, S. Becker, S. Thrun, and K. Obermayer, eds. MIT Press. pp. 1327-1334.

Liets LC, Olshausen BA, Wang GY, Chalupa LM (2003). Spontaneous activity of morphologically identified ganglion cells in the developing ferret retina. The Journal of Neuroscience, 23(15), 7343-50.

Murray SO, Olshausen BA, Woods DL (2003) Processing shape, motion, and three- dimension shape-from-motion in the human cortex. Cerebral Cortex, 13(5), 508-16.

Murray SO, Kersten D, Olshausen BA, Schrater P, Woods DL (2002) Shape percep- tion reduces activity in human primary visual cortex. Proceedings of the National Academy of Sciences, USA, 99(23): 15164-15169.

Press WA, Olshausen BA, Van Essen DC (2001) A graphical anatomical database of neural connectivity. Philosophical Transactions of the Royal Society, B, 356, 1147- 1157. Olshausen BA, Sallee P, Lewicki MS (2001). Learning sparse image codes using a wavelet pyramid architecture. In: Advances in Neural Information Processing Systems, 13, T.K. Leen, T.G. Dietterich, V. Tresp, eds. MIT Press. pp. 887-893.

Olshausen BA (2000). Sparse coding of time-varying natural images. ICA2000 Pro- ceedings, June 19-22, 2000, Helsinki, Finland. P. Pajunen and J. Karhunen, eds, pp. 603-608.

Olshausen BA, Millman KJ (2000). Learning sparse codes with a mixture-of-Gaussians prior. In: Advances in Neural Information Processing Systems, 12, S.A. Solla, T.K. Leen, K.R. Muller, eds. MIT Press, pp. 841-847.

Lewicki MS, Olshausen BA (1999). A probabilistic framework for the adaptation and comparison of image codes. Journal of the Optical Society of America A, 16, 1587- 1601.

Wang GY, Olshausen BA, Chalupa LM (1999) Differential effects of Apamin- and Charybdotoxin-sensitive K+ conductances on spontaneous discharge patterns of developing retinal ganglion cells. The Journal of Neuroscience, 19, 2609-2618.

Lewicki MS, Olshausen BA (1998). Inferring sparse, overcomplete image codes using an efficient coding framework. In: Advances in Neural Information Processing Systems, 10, M.I. Jordan, M.J. Kearns, S.A. Solla, eds. MIT Press.

Olshausen BA, Field DJ (1997). Sparse coding with an overcomplete basis set: A strategy employed by V1? Vision Research, 37, 3311-3325.

Olshausen BA, Field DJ (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381, 607-609.

Olshausen BA, Field DJ (1996). Natural image statistics and efficient coding. Network, 7, 333-339.

Lee CW, Olshausen BA (1996). A nonlinear Hebbian network that learns to detect disparity in random-dot stereograms. Neural Computation, 8, 573-594.

Olshausen BA, Anderson CH, Van Essen DC (1995). A multiscale routing circuit for forming size- and position-invariant object representations. The Journal of Com- putational Neuroscience, 2, 45-62.

Olshausen BA, Anderson CH, Van Essen DC (1993). A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of informa- tion. The Journal of Neuroscience, 13(11), 4700-4719.

Van Essen DC, Olshausen B, Anderson CH, Gallant JL (1991). Pattern recognition, attention, and information bottlenecks in the primate visual system. In: Proc. SPIE Conf. on Visual Information Processing: From Neurons to Chips, 1473, p. 17-28. Invited papers, reviews and opinions:

Olshausen BA (2014) Perception as an inference problem. In: The Cognitive Neuro- sciences V, M. Gazzaniga, R. Mangun, Eds. MIT Press.

Olshausen BA, Lewicki MS (2013) What natural scene statistics can tell us about cor- tical representation. In: The New Visual Neurosciences. J. Werner, L.M. Chalupa, Eds. MIT Press.

Olshausen BA (2012) 20 years of learning about vision: Questions answered, Ques- tions unanswered, and Questions not yet asked. In: 20 Years of Computational Neuroscience. J. Bower, Ed. Springer.

Olshausen BA, Anderson CH (2010) Does the brain de-jitter retinal images? Proceedings of the National Academy of Sciences (Commentary), 107(46):19607-8.

Olshausen BA, DeWeese MR (2010) The statistics of style. Nature (News & Views), 463: 1027-8.

Teeters JL, Harris KD, Millman KJ, Olshausen BA, Sommer FT (2008) Data sharing for computational neuroscience. Neuroinformatics, 6(1), 47-55.

Carandini M, Demb JB, Mante V, Tolhurst DJ, Dan Y, Olshausen BA, Gallant JL, Rust NC (2005) Do we know what the early visual system does? J Neurosci, 25(46), 10577-97.

Olshausen BA, Field DJ (2004) Sparse coding of sensory inputs. Current Opinion in Neurobiology, 14: 481-487.

Olshausen BA (2003) Principles of image representation in visual cortex. In: The Visual Neurosciences, L.M. Chalupa, J.S. Werner, Eds. MIT Press. pp. 1603-15.

Olshausen BA, O’Connor KN (2002). A new window on sound. Nature Neuroscience, 5, 292-293.

Olshausen BA (2002) Forward. Map-seeking circuits in visual cognition. Stanford Uni- versity Press. pp. xiii-xiv.

Olshausen BA (2002) Review of ‘Theoretical Neuroscience: Computational and Math- ematical Modeling of Neural Systems,’ by Peter Dayan and L.F. Abbott. Journal of Cognitive Neuroscience, 15(1): 154-155.

Simoncelli EP, Olshausen BA (2001). Natural image statistics and neural representa- tion. Annual Reviews of Neuroscience, 24, 1193-1215.

Olshausen BA, Field DJ (2000). Vision and the coding of natural images. American Scientist, 88, 238-245.

Conference proceedings and book chapters: Anderson AG, Ratnam K, Roorda A, Olshausen BA (2016) A Neural Model of High- Acuity Vision in the Presence of Fixational Eye Movements. 50th Asilomar Con- ference on Signals, Systems and Computers, November 6-9, 2016. IEEE Signal Processing Society.

Cheung B, Weiss E, Olshausen BA (2016) Learning retinal tiling in a model of visual attention. International Conference on Learning Representations 2016 Workshop.

Cheung B, Livezey JA, Bansal AK, Olshausen BA (2015) Discovering hidden factors of variation in deep networks. International Conference on Learning Representations 2015 Workshop. arXiv:1412.6583v4

Olshausen BA (2013) Highly overcomplete sparse coding. In: SPIE Proceedings vol. 8651: Human Vision and Electronic Imaging XVIII, (B.E. Rogowitz, T.N. Pappas, H. de Ridder, Eds.), Feb. 4-7, 2013, San Francisco, California.

Abbey CK, Sohl-Dickstein JN, Olshausen BA, Eckstein MP, Boone JM (2009) Higher- order scene statistics of breast images. In: Proc. SPIE 7263, Medical Imag- ing 2009: Image Perception, Observer Performance, and Technology Assessment, 726317 (March 12, 2009).

Olshausen BA, Cadieu CF, Warland DK (2009) Learning real and complex overcomplete representations from the statistics of natural images. In: SPIE Proceedings, Vol. 7446: Wavelets XIII, (V.K. Goyal, M. Papadakis, D. van de Ville, Eds.), August 2-4, 2009, San Diego, California.

Olshausen BA, Cadieu CF, Culpepper J, Warland DK (2007) Bilinear models of natural images. In: SPIE Proceedings vol. 6492: Human Vision and Electronic Imaging XII, (B.E. Rogowitz, T.N. Pappas, S.J. Daly, Eds.), Jan 28-Feb 1, 2007, San Jose, California.

Olshausen BA, Field DJ (2004) What is the other 85% of V1 doing? In: 23 Problems in Systems Neuroscience. T.J. Sejnowski, L. van Hemmen, eds. Oxford University Press.

Van Essen DC, Olshausen BA, Anderson CH (2003) Directed visual attention and the dynamic control of information flow. In: Encyclopedia of Visual Attention, Itti, Rees, Tsotsos, eds.

Olshausen BA (2002). Sparse codes and spikes. In: R.P.N. Rao, B.A. Olshausen, M.S. Lewicki (Eds.), Probabilistic Models of Perception and Brain Function, pp. 257-272. MIT Press.

Olshausen BA, Koch C (1995). Selective visual attention. In M. Arbib (Ed.), The Handbook of Brain Theory and Neural Networks. MIT Press.

Anderson CH, Olshausen BA, Van Essen DC (1995). Dynamic routing networks. In M. Arbib (Ed.), The Handbook of Brain Theory and Neural Networks. MIT Press. Olshausen BA, Anderson CH (1995) A model of the spatial-frequency organization in primate striate cortex. The Neurobiology of Computation: Proceedings of the Third Annual Computation and Neural Systems Conference. J.M. Bower, Ed., Boston: Kluwer Academic Publishers, pp. 275-280.

Van Essen DC, Anderson CH, Olshausen BA (1994). Dynamic routing strategies in sensory, motor, and cognitive processing. In: C. Koch and J. Davis (Eds.), Large Scale Neuronal Theories of the Brain. MIT Press.

Van Essen DC, Olshausen B, Gallant J, Press W, Anderson C, Drury H, Carmen G, Felleman D (1994) Anatomical, physiological, and computational aspects of hierar- chical processing in the macaque visual cortex. In: C. Nothdurft (Ed.), Structural and Functional Organization of the Neocortex. (Festschrift for Otto Creuzfeldt, Gottingen, Germany).

Technical reports:

K¨osterU, Olshausen BA (2013) Testing our conceptual understanding of V1 function. arXiv:1311.0778

Sohl-Dickstein J, Wang CM, Olshausen BA (2010) An Unsupervised Algorithm For Learning Lie Group Transformations. arXiv:1001.1027

Olshausen BA (1996). Learning linear, sparse, factorial codes. AI Memo 1580, Artificial Intelligence Laboratory, Massachusetts Institute of Technology.

Olshausen BA, Anderson CH, Van Essen DC (1992). A neural model of visual atten- tion and invariant pattern recognition. CNS Memo 18, Computation and Neural Systems Program, California Institute of Technology.

Olshausen BA (1988). A survey of visual preprocessing and shape representation tech- niques. RIACS Technical Report 88.35, Research Institute for Advanced Computer Science, NASA Ames Research Center.

Abstracts/Presentations:

Khosrowshahi A, Baker J, Yen SC, Gray CM, Olshausen BA (2007) Predicting responses of V1 neurons to natural movies. Society for Neuroscience Abstracts, 33

Olshausen BA (2005) What does 85% of V1 do? Society for Neuroscience Minisympo- sium - “Do we know what the early visual system does?”.

Olshausen BA, Baker J, Yen S, Gray CM (2004) Receptive field models fail to predict responses of V1 neurons to natural movies. Society for Neuroscience Abstracts, 30.

Johnson JS, Olshausen BA (2002) Early target related processing in the discrimination of natural objects. Vision Sciences Society Second Annual Meeting, abstract 695. Olshausen BA (2001) Sparse coding of time-varying natural images. Society for Neuro- science Abstracts, 27.

Murray SO, Olshausen BA, Alho K, Woods DL (2001) Shape perception reduces activity in human primary visual cortex. Society for Neuroscience Abstracts, 27.

Johnson JS, Town WL, Olshausen BA (2000) Effects of occlusion on the speed of visual processing of natural scenes. Society for Neuroscience Abstracts, 26.

Murray SO, Olshausen BA, Woods DL (2000) Activation of human visual cortex by motion-defined three-dimensional shape. Cognitive Neuroscience Society Annual Meeting.

Johnson JS, Guirao J, Olshausen BA (1999) Early neurophysiological correlates of object recognition in natural images, Investigative Opthalmology and Visual Science, 40, S822.

Olshausen BA (1998) Learning sparse image codes via convolution. Computation and Neural Systems meeting, Santa Barbara, CA, July 26-30.

Olshausen BA (1997) A functional model of V1 horizontal connectivity based on the statistical structure of natural images. Society for Neuroscience Abstracts, 23, 2363.

Olshausen BA, Field DJ (1996) Encoding of contours in natural images. Computation and Neural Systems meeting, Cambridge, MA, July 14-17.

Olshausen BA, Field DJ (1996) Relations between the “association field” and the statis- tics of natural scenes. Investigative Opthalmology and Visual Science, 37, S517.

Olshausen BA, Field DJ (1995) A model for the development of orientation selectivity based on early spontaneous activity. Society for Neuroscience Abstracts, 21, 2025.

Olshausen BA, Field DJ (1995) Learning localized, oriented, multiscale receptive fields from natural scenes. Computation and Neural Systems meeting, Monterey, Califor- nia, July 12-15.

Olshausen BA, Anderson CH (1994) A model of the spatial-frequency organization in primate visual cortex. Computation and Neural Systems meeting, Monterey, California, July 21-23.

Press WA, Olshausen BA, Van Essen DC (1993) Analyzing connections between the pulvinar and visual cortex: An interactive graphical database. Society for Neuro- science Abstracts, 19, 331.

Olshausen BA, Anderson CH, Van Essen DC (1992) Computer simulation of a dynamic routing model of visual attention. Investigative Opthalmology and Visual Science, 33(4), 1263. Invited Talks and Colloquia

Institut f¨urNeuroinformatik, Ruhr-Universit¨atBochum, July 1992 Department of Computer Science, University of Toronto, January 1993 Department of Anatomy and Neurobiology, Washington University, April 1993 Beckman Institute, University of Illinois, Urbana-Champaign, February 1994 Center for Biological and Computational Learning, MIT, May 1994 Gordon Research Conference, Tilton School, New Hampshire, June 1996 Workshop on Visual Attention, University of Toronto/CIAR, November 1996 Communications Research Laboratory, Kobe, Japan, March 1997 RIKEN Brain Information Processing Group, Wako-shi, Japan 1997 Vision Science Program, U.C. Berkeley, April 1997 Computation and Neural Systems meeting, Big Sky, Montana, July 1997 Workshop on Principles of Behaving Systems, Cambridge, UK, October 1997 Max-Planck Institute for Biological Cybernetics, T¨ubingen, Germany, October 1997. Smith-Kettlewell Eye Research Institute, San Francisco, April 1998 Committee on Neurobiology, University of Chicago, June 1998 Sloan Computational Neuroscience meeting, California Institute of Technology, July 1998 Department of Physics, California State University at Sacramento, October 1998 Dartmouth Mind Brain Symposium, Dartmouth, New Hampshire, January 1999 Division of Neuroscience, Baylor College of Medicine, February 1999 Center for the Neural Basis of Cognition, Carnegie-Mellon University, March 1999 Gatsby Computational Neuroscience Unit, University College London, June 1999 Berlin Neuroscience Forum, Bogensee, Germany, July 1999 Dynamic Brain Forum, Asilomar, California, September 1999 Neuroscience Program, University of Maryland, College Park, April 2000 Sloan Foundation Gain Fields Workshop, Pajaro Dunes, California, May 2000 Neuroinformatics workshop, Japanese Neuroscience Society, Yokohama, September 2000 Network Models of Cognition, Banbury Center, Cold Spring Harbor Labs, September 2000 Natural Scene Statistics, Banbury Center, Cold Spring Harbor Labs, October 2000 Bayes 2001 workshop, Smith-Kettlewell Eye Research Institute, January 2001 Cognitive Science colloquium, UC Irvine, March 2001 Statistics Department seminar, UCLA, May 2001 Evolution and Plasticity of Neocortex, ICTP, Trieste, Italy, April 2001 Computational Neuroscience Summer School, ICTP, Trieste, Italy, August 2001 Neyman seminar, Department of Statistics, UC Berkeley, September 2001 Neuromorphic Engineering program seminar, Caltech, October 2001 Department of Physiology & Biophysics, University of Washington, October 2001 Computational Neuroscience Symposium, University of Minnesota, April 2002 Math Department Seminar, University of Wisconsin, Madison, April 2002 Neuromorphic Engineering Workshop, Telluride, Colorado, July 2002 Computational Neurobiology Laboratory, Salk Institute, October 2002 Department of Psychology, University of Nevada, Reno, November 2002 Ricoh Innovations, California Research Center, January 2003 Center for Visual Science Colloquium, University of Rochester, February 2003 Workshop on Neural Coding, MBI, Ohio-State University, February 2003 Computational Neuroscience Seminar, Washington Univ. School of Med., March 2003 Max-Planck-Institute for Neurobiology, Munich, Germany, September 2003 Workshop on Redundant Representations for Visual Communications, International Con- ference on Image Processing, Barcelona, Spain, September 2003 Stanford Brain Research Institute, October 2003 Center for Perceptual Systems, University of Texas, Austin, October 2003 National Academies Keck Futures Initiative Signaling Conference, Irvine, California, November 2003 James S. McDonnell Foundation workshop on Brain Energetics and Information Process- ing, Palisades, New York, November 2003 Graduate student selected seminar speaker, Center for Neuroscience, UC Davis, March 2004 Electrical Engineering and Computer Science seminar, UC Berkeley, April 2004 IBRO Latin American Neuroscience School, Santiago, Chile, May 2004 Computational neuroimaging workshop, Stanford University, July 2004 Multiscale Geometric Analysis workshop, Institute for Pure and Applied Mathematics, UCLA, September 2004 Computational Neuroscience School, Okinawa, Japan, November 2004 Mathematical Sciences Research Institute workshop on Neurobiological Vision, UC Berke- ley, February 2005 Ninth International Conference on Cognitive and Neural Systems, Tutorial lecture, Boston University, May 2005 Electrical and Computer Engineering seminar, Rice University, May 2005 IPAM summer school on Intelligent Extraction of Information from Graphs and High- Dimensional Data, UCLA, July 2005 Center for Theoretical Biological Physics summer school on Computational and experi- mental neurobiology, UC San Diego, August 2005 Graduate student selected seminar speaker, Neurobiology and Behavior program, Uni- versity of Washington, October 2005 NIPS tutorial on Natural Image Statistics and Biological Vision, Vancouver, BC, Decem- ber 2005 Complex Systems Summer School, Santa Fe Institute, June 26-30, 2006 Bernstein symposium, Humboldt University, Berlin, Germany, October 2006 Center for the Neural Basis of Cognition seminar, Carnegie-Mellon University, December 2006 Statistics Department seminar, UCLA, April 2007 Symposium on Natural Scene Understanding, Vision Sciences Society annual meeting, Sarasota, Florida, May 2007 Intelligence Community Academic Summit, Williamsburg, VA, June 2007 CIAR Summer School on Learning and Vision, University of Toronto, August 2007 Graduate student selected speaker, Neuroscience Program, UC San Diego, February 2008 Natural Environments, Tasks, and Intelligence workshop, UT Austin, March 2008 Workshop on Biological Computation, Santa Fe Institute, May 2008 Connectionism and Probabilistic Models workshop, UC Berkeley, Aug. 7-9, 2008 Department of Psychology seminar, UC Santa Barbara, Nov. 14, 2008 Max-Planck Institute seminar, Tubingen, Germany, Feb. 3, 2009 Engineering Department seminar, University of Cambridge, March 4, 2009 Institute of Theoretical Physics, University of Bremen, Germany, May 4, 2009 Fakult¨atf¨urMathematik und Informatik seminar, University of Jena, May 14, 2009 Bernstein Center lecture, Ludwig-Maximilians Universitaet, Munich, May 25, 2009 Vision group seminar, University of Giessen, Germany, June 17, 2009 Institute f¨urNeuroinformatics seminar, ETH Zurich, Switzerland, June 19, 2009 Signal Processing Laboratory seminar, EPFL, Lausanne, Switzerland, June 22, 2009 Institut fur Neuro- und Bioinformatik, University of L¨ubeck, Germany, July 3, 2009 Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany, July 9, 2009 Medical Image Processing Systems Conference, Santa Barbara, California, October 19- 21, 2009 Center for Theoretical Neuroscience, Columbia University, New York, New York, March 12, 2010 Janelia Farms, Ashburn, Virginia, March 15, 2010 Keck Seminar, Rice University, Houston, Texas, April 16, 2010 Stanford Neuroscience Student Retreat, Monterey, California, May 1, 2010 Defense Sciences Research Council, Santa Cruz, California, July 13, 2010 Theoretical Neuroscience Symposium, University of Southern California, Los Angeles, California, January 7, 2011 Mind, Brain and Computation program, Stanford University, January 24, 2011 Grand Challenges in Neural Computation, Santa Fe, New Mexico, February 21-23, 2011 York Vision Conference, Center for Visual Science, York University, Toronto, Canada, June 18, 2011 Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland, August 29, 2011 Machine Learning and Neuroscience Symposium, Janelia Farm, Virginia, May 6-9, 2012 Distinguished Speaker Series, Cognitive Science Department, UCSD, May 14, 2012 Neuromorphic Engineering Workshop, Telluride, Colorado, July 6, 2012 Summer School on Deep Learning, Feature Learning, IPAM, UCLA, July 22-27, 2012 Sensory Coding and the Natural Environment, Institute of Science & Technology, Aus- tria, September 9-12, 2012 Department of Electrical Engineering seminar, Rice University, February 21, 2013 The Cognitive Neurosciences summer workshop, Lake Tahoe, June 29-July 1, 2013 NIH BRAIN panel on Computation, Theory and Big Data, Boston, MA, July 30, 2013 Bay Area Vision Meeting, Facebook, October 4, 2013 Symposium on the Role of Sparsity in Neural Computation and the Natural World, Stan- ford University, February 26, 2014 Department of Electrical Engineering seminar, Rice University, March 13, 2014 Department of Electrical Engineering seminar, Carnegie Mellon University, April 24, 2014 Leonardo Art Science Evening Rendezvous, University of San Francisco, May 5, 2014 Summer course on Computational Neuroscience: Vision, Cold Spring Harbor Labs, NY, July 18, 2014 CIFAR Summer School on Learning and Vision in Biology and Engineering, University of Toronto, August 16, 2014 Department of Psychology seminar, Cornell University, August 18, 2014 Computing Community Consortium BRAIN workshop, Washington, DC, Dec 3-5, 2014 Center for Vision Research, Brown University, April 8, 2015 Department of Brain and Cognitive Sciences seminar, MIT, April 9, 2015 Keynote Lecture, Vision Sciences Society annual meeting, May 16, 2015 Computational Vision Summer School, Freudenstadt, Germany, August 4, 2015 Neuro-Inspired Computaitonal Elements workshop, UC Berkeley, March 2016 Computation & Neural Systems seminar, California Institute of Technology, April 2016 Deep Learning Summer School, University of Montreal, August 2016 IEEE CEDA, Design Automation Futures Workshop, San Jose, CA, October 2016 Neuro-Inspired Computational Elements workshop, IBM Almaden, March 6, 2017 Theoretical Neuroscience Day, Georgia Institute of Technology, March 15, 2017 Interdisciplinary Mind and Brain Seminar, University of Pennsylvania, March 17, 2017 Machine Learning Workshop, Simons Institute, UC Berkeley, March 31, 2017 Allerton Conference on Communication, Control and Computing, October 2017 France-Stanford Center workshop on Brain-Inspired Computing, October 2017 Workshop on Neuro-Inspired Computing Using Nanoelectronic Devices, UC San Diego, October 2017 Workshop on Computational Theories of the Brain, Simons Institute for the Theory of Computing, UC Berkeley, April 2018 Workshop on Computational Neuroscience, Flatiron Institute, New York, April 2018 Seminar, BRI Visual Neurosciences Affinity Group, UCLA, June 2018 Keynote talk, Collaborative Research in Computational Neuroscience meeting, Berkeley, June 2018 Keynote talk, Symposium on the Theory of Computing, Los Angeles, June 2018 Gordon Research Conference, Neurobiology of Cognition, Sunday River, Maine, July 2018 Workshop on Artificial Intelligence and the Barrier of Meaning, Santa Fe Institute, Oc- tober 2018 Arthur M. Sackler Colloquium on The Science of Deep Learning, National Academy of Sciences, March 2019 Psychological and Brain Sciences Colloquium, Dartmouth College, March 2019 Workshop on Natural Environments, Tasks and Intelligence, UT Austin, April 2019