Bruno A. Olshausen

Publication Activity (10 Years)

Years Active: 1993-2023
Publications (10 Years): 58

Top Topics

Distributed Representations

Top Venues

Publications

Denis Kleyko, Connor Bybee, Ping-Chen Huang, Christopher J. Kymn, Bruno A. Olshausen, Edward Paxon Frady, Friedrich T. Sommer
Efficient Decoding of Compositional Structure in Holistic Representations. Neural Comput. 35 (7) (2023)
Denis Kleyko, Connor Bybee, Ping-Chen Huang, Christopher J. Kymn, Bruno A. Olshausen, Edward Paxon Frady, Friedrich T. Sommer
Efficient Decoding of Compositional Structure in Holistic Representations. CoRR (2023)
Christian Shewmake, Nina Miolane, Bruno A. Olshausen
Group Equivariant Sparse Coding. GSI (1) (2023)
Edward Paxon Frady, Spencer J. Kent, Quinn Tran, Pentti Kanerva, Bruno A. Olshausen, Friedrich T. Sommer
Learning and generalization of compositional representations of visual scenes. CoRR (2023)
Zeyu Yun, Juexiao Zhang, Bruno A. Olshausen, Yann LeCun, Yubei Chen
URLOST: Unsupervised Representation Learning without Stationarity or Topology. CoRR (2023)
Trenton Bricken, Rylan Schaeffer, Bruno A. Olshausen, Gabriel Kreiman
Emergence of Sparse Representations from Noise. ICML (2023)
Christopher J. Kymn, Denis Kleyko, Edward Paxon Frady, Connor Bybee, Pentti Kanerva, Friedrich T. Sommer, Bruno A. Olshausen
Computing with Residue Numbers in High-Dimensional Representation. CoRR (2023)
Yubei Chen, Zeyu Yun, Yi Ma, Bruno A. Olshausen, Yann LeCun
Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform. ICLR (2023)
Sophia Sanborn, Christian Shewmake, Bruno A. Olshausen, Christopher J. Hillar
Bispectral Neural Networks. ICLR (2023)
Marissa Connor, Bruno A. Olshausen, Christopher Rozell
Learning Internal Representations of 3D Transformations from 2D Projected Inputs. CoRR (2023)
Yubei Chen, Zeyu Yun, Yi Ma, Bruno A. Olshausen, Yann LeCun
Minimalistic Unsupervised Learning with the Sparse Manifold Transform. CoRR (2022)
Hong-Ye Hu, Dian Wu, Yi-Zhuang You, Bruno A. Olshausen, Yubei Chen
RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior. Mach. Learn. Sci. Technol. 3 (3) (2022)
Denis Kleyko, Connor Bybee, Christopher J. Kymn, Bruno A. Olshausen, Amir Khosrowshahi, Dmitri E. Nikonov, Friedrich T. Sommer, Edward Paxon Frady
Integer Factorization with Compositional Distributed Representations. CoRR (2022)
Ho Yin Chau, Frank Qiu, Yubei Chen, Bruno A. Olshausen
Disentangling images with Lie group transformations and sparse coding. NeurReps (2022)
Ping-Chen Huang, Denis Kleyko, Jan M. Rabaey, Bruno A. Olshausen, Pentti Kanerva
Computing with Hypervectors for Efficient Speaker Identification. CoRR (2022)
Sophia Sanborn, Christian Shewmake, Bruno A. Olshausen, Christopher Hillar
Bispectral Neural Networks. CoRR (2022)
Xin Zheng, Ryan Zarcone, Akash Levy, Win-San Khwa, Priyanka Raina, Bruno A. Olshausen, H.-S. Philip Wong
High-density analog image storage in an analog-valued non-volatile memory array. Neuromorph. Comput. Eng. 2 (4) (2022)
Evgenya Pergament, Pulkit Tandon, Kedar Tatwawadi, Oren Rippel, Lubomir D. Bourdev, Bruno A. Olshausen, Tsachy Weissman, Sachin Katti, Alexander G. Anderson
An Interactive Annotation Tool for Perceptual Video Compression. QoMEX (2022)
Michael Y.-S. Fang, Mayur Mudigonda, Ryan Zarcone, Amir Khosrowshahi, Bruno A. Olshausen
Learning and Inference in Sparse Coding Models With Langevin Dynamics. Neural Comput. 34 (8) (2022)
Connor Bybee, Denis Kleyko, Dmitri E. Nikonov, Amir Khosrowshahi, Bruno A. Olshausen, Friedrich T. Sommer
Efficient Optimization with Higher-Order Ising Machines. CoRR (2022)
Edward Paxon Frady, Denis Kleyko, Christopher J. Kymn, Bruno A. Olshausen, Friedrich T. Sommer
Computing on Functions Using Randomized Vector Representations (in brief). NICE (2022)
Denis Kleyko, Connor Bybee, Christopher J. Kymn, Bruno A. Olshausen, Amir Khosrowshahi, Dmitri E. Nikonov, Friedrich T. Sommer, Edward Paxon Frady
Integer Factorization with Compositional Distributed Representations. NICE (2022)
Alpha Renner, Lazar Supic, Andreea Danielescu, Giacomo Indiveri, Bruno A. Olshausen, Yulia Sandamirskaya, Friedrich T. Sommer, Edward Paxon Frady
Neuromorphic Visual Scene Understanding with Resonator Networks. CoRR (2022)
Denis Kleyko, Mike Davies, Edward Paxon Frady, Pentti Kanerva, Spencer J. Kent, Bruno A. Olshausen, Evgeny Osipov, Jan M. Rabaey, Dmitri A. Rachkovskij, Abbas Rahimi, Friedrich T. Sommer
Vector Symbolic Architectures as a Computing Framework for Emerging Hardware. Proc. IEEE 110 (10) (2022)
Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR (2022)
Michael Y.-S. Fang, Mayur Mudigonda, Ryan Zarcone, Amir Khosrowshahi, Bruno A. Olshausen
Learning and Inference in Sparse Coding Models with Langevin Dynamics. CoRR (2022)
Zeyu Yun, Yubei Chen, Bruno A. Olshausen, Yann LeCun
Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors. DeeLIO@NAACL-HLT (2021)
Denis Kleyko, Mike Davies, Edward Paxon Frady, Pentti Kanerva, Spencer J. Kent, Bruno A. Olshausen, Evgeny Osipov, Jan M. Rabaey, Dmitri A. Rachkovskij, Abbas Rahimi, Friedrich T. Sommer
Vector Symbolic Architectures as a Computing Framework for Nanoscale Hardware. CoRR (2021)
Cameron Diao, Denis Kleyko, Jan M. Rabaey, Bruno A. Olshausen
Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing. CoRR (2021)
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno A. Olshausen, Trevor Darrell
Tent: Fully Test-Time Adaptation by Entropy Minimization. ICLR (2021)
Zeyu Yun, Yubei Chen, Bruno A. Olshausen, Yann LeCun
Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors. CoRR (2021)
Cameron Diao, Denis Kleyko, Jan M. Rabaey, Bruno A. Olshausen
Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing. IJCNN (2021)
Edward Paxon Frady, Denis Kleyko, Christopher J. Kymn, Bruno A. Olshausen, Friedrich T. Sommer
Computing on Functions Using Randomized Vector Representations. CoRR (2021)
Edward Paxon Frady, Spencer J. Kent, Bruno A. Olshausen, Friedrich T. Sommer
Resonator networks for factoring distributed representations of data structures. CoRR (2020)
Hong-Ye Hu, Dian Wu, Yi-Zhuang You, Bruno A. Olshausen, Yubei Chen
RG-Flow: A hierarchical and explainable flow model based on renormalization group and sparse prior. CoRR (2020)
Ho Yin Chau, Frank Qiu, Yubei Chen, Bruno A. Olshausen
Disentangling images with Lie group transformations and sparse coding. CoRR (2020)
Dylan M. Paiton, Steven Shepard, Kwan Ho Ryan Chan, Bruno A. Olshausen
Subspace Locally Competitive Algorithms. NICE (2020)
Spencer J. Kent, Edward Paxon Frady, Friedrich T. Sommer, Bruno A. Olshausen
Resonator Networks, 2: Factorization Performance and Capacity Compared to Optimization-Based Methods. Neural Comput. 32 (12) (2020)
Edward Paxon Frady, Spencer J. Kent, Bruno A. Olshausen, Friedrich T. Sommer
Resonator Networks, 1: An Efficient Solution for Factoring High-Dimensional, Distributed Representations of Data Structures. Neural Comput. 32 (12) (2020)
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno A. Olshausen, Trevor Darrell
Fully Test-time Adaptation by Entropy Minimization. CoRR (2020)
Spencer J. Kent, Edward Paxon Frady, Friedrich T. Sommer, Bruno A. Olshausen
Resonator Circuits for factoring high-dimensional vectors. CoRR (2019)
Juexiao Zhang, Yubei Chen, Brian Cheung, Bruno A. Olshausen
Word Embedding Visualization Via Dictionary Learning. CoRR (2019)
Brian Cheung, Alexander Terekhov, Yubei Chen, Pulkit Agrawal, Bruno A. Olshausen
Superposition of many models into one. NeurIPS (2019)
Dequan Wang, Evan Shelhamer, Bruno A. Olshausen, Trevor Darrell
Dynamic Scale Inference by Entropy Minimization. CoRR (2019)
Shariq Mobin, Bruno A. Olshausen
Auditory Separation of a Conversation from Background via Attentional Gating. CoRR (2019)
Brian Cheung, Alexander Terekhov, Yubei Chen, Pulkit Agrawal, Bruno A. Olshausen
Superposition of many models into one. CoRR (2019)
Yubei Chen, Dylan M. Paiton, Bruno A. Olshausen
The Sparse Manifold Transform. NeurIPS (2018)
Yubei Chen, Dylan M. Paiton, Bruno A. Olshausen
The Sparse Manifold Transform. CoRR (2018)
Shariq Mobin, Brian Cheung, Bruno A. Olshausen
Convolutional vs. Recurrent Neural Networks for Audio Source Separation. CoRR (2018)
Ryan Zarcone, Dylan M. Paiton, Alex Anderson, Jesse H. Engel, H.-S. Philip Wong, Bruno A. Olshausen
Joint Source-Channel Coding with Neural Networks for Analog Data Compression and Storage. DCC (2018)
Jan M. Rabaey, Abbas Rahimi, Sohum Datta, Miles Rusch, Pentti Kanerva, Bruno A. Olshausen
Human-centric computing - The case for a Hyper-Dimensional approach. IWASI (2017)
Brian Cheung, Eric Weiss, Bruno A. Olshausen
Emergence of foveal image sampling from learning to attend in visual scenes. ICLR (Poster) (2017)
Jesse H. Engel, Sukru Burc Eryilmaz, SangBum Kim, Matthew BrightSky, Chung Lam, Hsiang-Lan Lung, Bruno A. Olshausen, H.-S. Philip Wong
Opportunities for Analog Coding in Emerging Memory Systems. CoRR (2017)
Abbas Rahimi, Sohum Datta, Denis Kleyko, Edward Paxon Frady, Bruno A. Olshausen, Pentti Kanerva, Jan M. Rabaey
High-Dimensional Computing as a Nanoscalable Paradigm. IEEE Trans. Circuits Syst. I Regul. Pap. (9) (2017)
Alexander G. Anderson, Cory P. Berg, Daniel P. Mossing, Bruno A. Olshausen
DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies. CoRR (2016)
Alexander G. Anderson, Bruno A. Olshausen, Kavitha Ratnam, Austin Roorda
A neural model of high-acuity vision in the presence of fixational eye movements. ACSSC (2016)
Brian Cheung, Eric Weiss, Bruno A. Olshausen
Emergence of foveal image sampling from learning to attend in visual scenes. CoRR (2016)
Brian Cheung, Jesse A. Livezey, Arjun K. Bansal, Bruno A. Olshausen
Discovering Hidden Factors of Variation in Deep Networks. ICLR (Workshop) (2015)
Urs Köster, Jascha Sohl-Dickstein, Charles M. Gray, Bruno A. Olshausen
Modeling Higher-Order Correlations within Cortical Microcolumns. PLoS Comput. Biol. 10 (7) (2014)
Bruno A. Olshausen
Highly overcomplete sparse coding. Human Vision and Electronic Imaging (2013)
Urs Köster, Bruno A. Olshausen, Charles M. Gray
Modeling neural population data. ACSSC (2013)
Charles F. Cadieu, Bruno A. Olshausen
Learning Intermediate-Level Representations of Form and Motion from Natural Movies. Neural Comput. 24 (4) (2012)
Benjamin J. Culpepper, Jascha Sohl-Dickstein, Bruno A. Olshausen
Building a better probabilistic model of images by factorization. ICCV (2011)
Ivana Tosic, Bruno A. Olshausen, Benjamin J. Culpepper
Learning Sparse Representations of Depth. IEEE J. Sel. Top. Signal Process. 5 (5) (2011)
Ching Ming Wang, Jascha Sohl-Dickstein, Ivana Tosic, Bruno A. Olshausen
Lie Group Transformation Models for Predictive Video Coding. DCC (2011)
Adam S. Charles, Bruno A. Olshausen, Christopher J. Rozell
Learning Sparse Codes for Hyperspectral Imagery. IEEE J. Sel. Top. Signal Process. 5 (5) (2011)
Jascha Sohl-Dickstein, Jimmy C. Wang, Bruno A. Olshausen
An Unsupervised Algorithm For Learning Lie Group Transformations CoRR (2010)
Pierre Garrigues, Bruno A. Olshausen
Group Sparse Coding with a Laplacian Scale Mixture Prior. NIPS (2010)
Ivana Tosic, Bruno A. Olshausen, Benjamin J. Culpepper
Learning sparse representations of depth CoRR (2010)
Benjamin J. Culpepper, Bruno A. Olshausen
Learning transport operators for image manifolds. NIPS (2009)
Charles F. Cadieu, Bruno A. Olshausen
Learning Transformational Invariants from Natural Movies. NIPS (2008)
Christopher J. Rozell, Don H. Johnson, Richard G. Baraniuk, Bruno A. Olshausen
Sparse Coding via Thresholding and Local Competition in Neural Circuits. Neural Comput. 20 (10) (2008)
Jeffrey L. Teeters, Kenneth D. Harris, K. Jarrod Millman, Bruno A. Olshausen, Friedrich T. Sommer
Data Sharing for Computational Neuroscience. Neuroinformatics 6 (1) (2008)
Pierre Garrigues, Bruno A. Olshausen
Learning Horizontal Connections in a Sparse Coding Model of Natural Images. NIPS (2007)
Bruno A. Olshausen, Charles F. Cadieu, Jack Culpepper, David K. Warland
Bilinear models of natural images. Human Vision and Electronic Imaging (2007)
Christopher J. Rozell, Don H. Johnson, Richard G. Baraniuk, Bruno A. Olshausen
Locally Competitive Algorithms for Sparse Approximation. ICIP (4) (2007)
Issac J. Trotts, Bruno A. Olshausen, Edward Jones
Neuroanatomical image alignment. IEEE Visualization (2005)
Bruno A. Olshausen, David J. Field
How Close Are We to Understanding V1? Neural Comput. 17 (8) (2005)
Fabien Vivodtzev, Lars Linsen, Georges-Pierre Bonneau, Bernd Hamann, Kenneth I. Joy, Bruno A. Olshausen
Hierarchical Isosurface Segmentation Based on Discrete Curvature. VisSym (2003)
Bruno A. Olshausen
Learning sparse, overcomplete representations of time-varying natural images. ICIP (1) (2003)
Phil Sallee, Bruno A. Olshausen
Image denoising using learned overcomplete representations. ICIP (3) (2003)
Phil Sallee, Bruno A. Olshausen
Learning Sparse Multiscale Image Representations. NIPS (2002)
Bruno A. Olshausen, Phil Sallee, Michael S. Lewicki
Learning Sparse Image Codes using a Wavelet Pyramid Architecture. NIPS (2000)
Bruno A. Olshausen, K. Jarrod Millman
Learning Sparse Codes with a Mixture-of-Gaussians Prior. NIPS (1999)
Michael S. Lewicki, Bruno A. Olshausen
Inferring Sparse, Overcomplete Image Codes Using an Efficient Coding Framework. NIPS (1997)
Bruno A. Olshausen, David J. Field
Learning efficient linear codes for natural images: the roles of sparseness, overcompleteness, and statistical independence. Human Vision and Electronic Imaging (1996)
David J. Field, Bruno A. Olshausen, Nuala Brady
Wavelets, blur, and the sources of variability in the amplitude spectra of natural scenes. Human Vision and Electronic Imaging (1996)
C. W. Lee, Bruno A. Olshausen
A nonlinear Hebbian network that learns to detect disparity in random- dot stereograms. Neural Comput. 8 (3) (1996)
Bruno A. Olshausen, Charles H. Anderson, David C. Van Essen
A multiscale dynamic routing circuit for forming size- and position-invariant object representations. J. Comput. Neurosci. 2 (1) (1995)
Ernst Niebur, Bruno A. Olshausen
Neurobiology, Psychophysics, and Computational Models of Visual Attention. NIPS (1993)