| Learning and Inference in Sparse Coding Models With Langevin Dynamics | 0 | 0.34 | 2022 |
| Integer Factorization with Compositional Distributed Representations. | 1 | 0.34 | 2022 |
| RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior | 0 | 0.34 | 2022 |
| Vector Symbolic Architectures as a Computing Framework for Emerging Hardware | 0 | 0.34 | 2022 |
| Tent: Fully Test-Time Adaptation by Entropy Minimization | 0 | 0.34 | 2021 |
| Transformer visualization via dictionary learning - contextualized embedding as a linear superposition of transformer factors. | 0 | 0.34 | 2021 |
| Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing | 0 | 0.34 | 2021 |
| Tent: Fully Test-Time Adaptation by Entropy Minimization. | 0 | 0.34 | 2021 |
| Subspace Locally Competitive Algorithms. | 0 | 0.34 | 2020 |
| Auditory Separation of a Conversation from Background via Attentional Gating. | 0 | 0.34 | 2019 |
| Superposition of many models into one. | 3 | 0.42 | 2019 |
| Resonator Circuits for factoring high-dimensional vectors. | 0 | 0.34 | 2019 |
| Joint Source-Channel Coding with Neural Networks for Analog Data Compression and Storage | 2 | 0.39 | 2018 |
| Convolutional vs. Recurrent Neural Networks for Audio Source Separation. | 0 | 0.34 | 2018 |
| The Sparse Manifold Transform. | 0 | 0.34 | 2018 |
| Emergence of foveal image sampling from learning to attend in visual scenes. | 0 | 0.34 | 2017 |
| Opportunities for Analog Coding in Emerging Memory Systems. | 0 | 0.34 | 2017 |
| High-Dimensional Computing as a Nanoscalable Paradigm. | 15 | 1.25 | 2017 |
| Human-centric computing — The case for a Hyper-Dimensional approach | 1 | 0.34 | 2017 |
| DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies. | 1 | 0.36 | 2016 |
| A Neural Model Of High-Acuity Vision In The Presence Of Fixational Eye Movements | 0 | 0.34 | 2016 |
| Emergence of foveal image sampling from learning to attend in visual scenes. | 0 | 0.34 | 2016 |
| Discovering Hidden Factors of Variation in Deep Networks. | 0 | 0.34 | 2015 |
| Discovering Hidden Factors of Variation in Deep Networks. | 32 | 1.60 | 2014 |
| Modeling Higher-Order Correlations Within Cortical Microcolumns | 9 | 0.60 | 2014 |
| Modeling Neural Population Data | 0 | 0.34 | 2013 |
| Learning intermediate-level representations of form and motion from natural movies | 27 | 1.41 | 2012 |
| Efficient methods for unsupervised learning of probabilistic models | 0 | 0.34 | 2012 |
| Lie Group Transformation Models for Predictive Video Coding | 1 | 0.45 | 2011 |
| Learning Sparse Codes for Hyperspectral Imagery. | 19 | 0.91 | 2011 |
| Learning sparse representations of depth | 11 | 0.54 | 2011 |
| Building a better probabilistic model of images by factorization | 8 | 1.32 | 2011 |
| Group Sparse Coding with a Laplacian Scale Mixture Prior. | 37 | 2.35 | 2010 |
| An Unsupervised Algorithm For Learning Lie Group Transformations | 6 | 0.67 | 2010 |
| Learning transport operators for image manifolds. | 5 | 0.48 | 2009 |
| Data Sharing for Computational Neuroscience. | 36 | 2.60 | 2008 |
| Sparse coding via thresholding and local competition in neural circuits | 121 | 9.60 | 2008 |
| Neuroanatomical image alignment | 0 | 0.34 | 2005 |
| How Close Are We to Understanding V1? | 81 | 9.24 | 2005 |
| Hierarchical isosurface segmentation based on discrete curvature | 13 | 0.94 | 2003 |
| Learning Sparse Multiscale Image Representations | 32 | 6.98 | 2002 |
| Inferring Sparse, Overcomplete Image Codes Using an Efficient Coding Framework. | 0 | 0.34 | 1997 |
| Inferring sparse, overcomplete image codes using an efficient coding framework | 21 | 14.83 | 1997 |
| A nonlinear hebbian network that learns to detect disparity in random-dot stereograms | 11 | 1.72 | 1996 |
| Neurobiology, Psychophysics, and Computational Models of Visual Attention | 0 | 0.34 | 1993 |
