Dmitri B. Chklovskii

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 58

Top Venues

CoRR

NeurIPS

ACSSC

Neural Comput.

Publications

Jason Moore, Alexander Genkin, Magnus Tournoy, Joshua Pughe-Sanford, Robert R. de Ruyter van Steveninck, Dmitri B. Chklovskii
The Neuron as a Direct Data-Driven Controller. CoRR (2024)
Siavash Golkar, Jules Berman, David Lipshutz, Robert Mihai Haret, Tim Gollisch, Dmitri B. Chklovskii
Neuronal Temporal Filters as Normal Mode Extractors. CoRR (2024)
Yanis Bahroun, Shagesh Sridharan, Atithi Acharya, Dmitri B. Chklovskii, Anirvan M. Sengupta
Unlocking the Potential of Similarity Matching: Scalability, Supervision and Pre-training. CoRR (2023)
Lyndon R. Duong, Eero P. Simoncelli, Dmitri B. Chklovskii, David Lipshutz
Adaptive whitening with fast gain modulation and slow synaptic plasticity. CoRR (2023)
Lyndon R. Duong, David Lipshutz, David J. Heeger, Dmitri B. Chklovskii, Eero P. Simoncelli
Statistical whitening of neural populations with gain-modulating interneurons. CoRR (2023)
Siavash Golkar, David Lipshutz, Tiberiu Tesileanu, Dmitri B. Chklovskii
An Online Algorithm for Contrastive Principal Component Analysis. ICASSP (2023)
Jingpeng Wu, Yicong Li, Nishika Gupta, Kazunori Shinomiya, Pat Gunn, Alexey Polilov, Hanspeter Pfister, Dmitri B. Chklovskii, Donglai Wei
An Out-of-Domain Synapse Detection Challenge for Microwasp Brain Connectomes. CoRR (2023)
Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta
Duality Principle and Biologically Plausible Learning: Connecting the Representer Theorem and Hebbian Learning. CoRR (2023)
Lyndon R. Duong, David Lipshutz, David J. Heeger, Dmitri B. Chklovskii, Eero P. Simoncelli
Adaptive Whitening in Neural Populations with Gain-modulating Interneurons. ICML (2023)
Lyndon R. Duong, Eero Simoncelli, Dmitri B. Chklovskii, David Lipshutz
Adaptive whitening with fast gain modulation and slow synaptic plasticity. NeurIPS (2023)
David Lipshutz, Aneesh Kashalikar, Shiva Farashahi, Dmitri B. Chklovskii
A linear discriminant analysis model of imbalanced associative learning in the mushroom body compartment. PLoS Comput. Biol. 19 (2) (2023)
David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii
A normative framework for deriving neural networks with multi-compartmental neurons and non-Hebbian plasticity. CoRR (2023)
David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii
Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation. ICLR (2023)
Siavash Golkar, Tiberiu Tesileanu, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
Constrained Predictive Coding as a Biologically Plausible Model of the Cortical Hierarchy. NeurIPS (2022)
David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii
Biologically plausible single-layer networks for nonnegative independent component analysis. Biol. Cybern. 116 (5) (2022)
Alexander Genkin, David Lipshutz, Siavash Golkar, Tiberiu Tesileanu, Dmitri B. Chklovskii
Biological Learning of Irreducible Representations of Commuting Transformations. NeurIPS (2022)
Siavash Golkar, David Lipshutz, Tiberiu Tesileanu, Dmitri B. Chklovskii
An online algorithm for contrastive Principal Component Analysis. CoRR (2022)
Jules Berman, Dmitri B. Chklovskii, Jingpeng Wu
Bridging the Gap: Point Clouds for Merging Neurons in Connectomics. MIDL (2022)
Tiberiu Tesileanu, Siavash Golkar, Samaneh Nasiri, Anirvan M. Sengupta, Dmitri B. Chklovskii
Neural Circuits for Dynamics-Based Segmentation of Time Series. Neural Comput. 34 (4) (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)
David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii
Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation. CoRR (2022)
David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii
A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis. Neural Comput. 33 (9) (2021)
Yanis Bahroun, Dmitri B. Chklovskii
A Neural Network with Local Learning Rules for Minor Subspace Analysis. CoRR (2021)
Jules Berman, Dmitri B. Chklovskii, Jingpeng Wu
Bridging the Gap: Point Clouds for Merging Neurons in Connectomics. CoRR (2021)
Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta
A Normative and Biologically Plausible Algorithm for Independent Component Analysis. NeurIPS (2021)
Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii
Neural optimal feedback control with local learning rules. NeurIPS (2021)
Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
A Similarity-preserving Neural Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit. CoRR (2021)
Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii
Neural optimal feedback control with local learning rules. CoRR (2021)
Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta
A Normative and Biologically Plausible Algorithm for Independent Component Analysis. CoRR (2021)
David Lipshutz, Charlie Windolf, Siavash Golkar, Dmitri B. Chklovskii
A biologically plausible neural network for Slow Feature Analysis. CoRR (2020)
David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii
A biologically plausible neural network for multi-channel Canonical Correlation Analysis. CoRR (2020)
David Lipshutz, Charles Windolf, Siavash Golkar, Dmitri B. Chklovskii
A Biologically Plausible Neural Network for Slow Feature Analysis. NeurIPS (2020)
David Lipshutz, Dmitri B. Chklovskii
Bio-NICA: A biologically inspired single-layer network for Nonnegative Independent Component Analysis. CoRR (2020)
Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
A biologically plausible neural network for local supervision in cortical microcircuits. CoRR (2020)
Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
A simple normative network approximates local non-Hebbian learning in the cortex. NeurIPS (2020)
Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
A simple normative network approximates local non-Hebbian learning in the cortex. CoRR (2020)
Cengiz Pehlevan, Xinyuan Zhao, Anirvan M. Sengupta, Dmitri B. Chklovskii
Neurons as Canonical Correlation Analyzers. Frontiers Comput. Neurosci. 14 (2020)
Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii
A Neural Network for Semi-Supervised Learning on Manifolds. CoRR (2019)
Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta
A Similarity-preserving Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit. NeurIPS (2019)
Amirhossein Khalilian-Gourtani, Mariano Tepper, Victor Minden, Dmitri B. Chklovskii
Strip the Stripes: Artifact Detection and Removal for Scanning Electron Microscopy Imaging. ICASSP (2019)
Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii
A Neural Network for Semi-supervised Learning on Manifolds. ICANN (1) (2019)
Cengiz Pehlevan, Dmitri B. Chklovskii
Neuroscience-Inspired Online Unsupervised Learning Algorithms: Artificial neural networks. IEEE Signal Process. Mag. 36 (6) (2019)
Cengiz Pehlevan, Dmitri B. Chklovskii
Neuroscience-inspired online unsupervised learning algorithms. CoRR (2019)
Mariano Tepper, Anirvan M. Sengupta, Dmitri B. Chklovskii
Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling. J. Mach. Learn. Res. 19 (2018)
Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii
Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics. ACSSC (2018)
Cengiz Pehlevan, Anirvan M. Sengupta, Dmitri B. Chklovskii
Why Do Similarity Matching Objectives Lead to Hebbian/Anti-Hebbian Networks? Neural Comput. 30 (1) (2018)
Anirvan M. Sengupta, Cengiz Pehlevan, Mariano Tepper, Alexander Genkin, Dmitri B. Chklovskii
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks. NeurIPS (2018)
Andrea Giovannucci, Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching. CoRR (2018)
Andrea Giovannucci, Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching. IEEE BigData (2018)
Cengiz Pehlevan, Sreyas Mohan, Dmitri B. Chklovskii
Blind nonnegative source separation using biological neural networks. CoRR (2017)
Andrea Giovannucci, Johannes Friedrich, Matt Kaufman, Anne Churchland, Dmitri B. Chklovskii, Liam Paninski, Eftychios A. Pnevmatikakis
OnACID: Online Analysis of Calcium Imaging Data in Real Time. NIPS (2017)
Cengiz Pehlevan, Sreyas Mohan, Dmitri B. Chklovskii
Blind Nonnegative Source Separation Using Biological Neural Networks. Neural Comput. 29 (11) (2017)
Mariano Tepper, Anirvan M. Sengupta, Dmitri B. Chklovskii
The surprising secret identity of the semidefinite relaxation of K-means: manifold learning. CoRR (2017)
Cengiz Pehlevan, Anirvan M. Sengupta, Dmitri B. Chklovskii
Adversarial synapses: Hebbian/anti-Hebbian learning optimizes min-max objectives. CoRR (2017)
Cengiz Pehlevan, Alexander Genkin, Dmitri B. Chklovskii
A clustering neural network model of insect olfaction. ACSSC (2017)
Reza Abbasi-Asl, Cengiz Pehlevan, Bin Yu, Dmitri B. Chklovskii
Do retinal ganglion cells project natural scenes to their principal subspace and whiten them? ACSSC (2016)
Yuansi Chen, Cengiz Pehlevan, Dmitri B. Chklovskii
Self-calibrating neural networks for dimensionality reduction. ACSSC (2016)
Yuansi Chen, Cengiz Pehlevan, Dmitri B. Chklovskii
Self-calibrating Neural Networks for Dimensionality Reduction. CoRR (2016)
Arjun Bharioke, Dmitri B. Chklovskii
Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit. PLoS Comput. Biol. 11 (8) (2015)
Cengiz Pehlevan, Dmitri B. Chklovskii
Optimization theory of Hebbian/anti-Hebbian networks for PCA and whitening. CoRR (2015)
Cengiz Pehlevan, Dmitri B. Chklovskii
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks. CoRR (2015)
Cengiz Pehlevan, Dmitri B. Chklovskii
A Hebbian/Anti-Hebbian Network Derived from Online Non-Negative Matrix Factorization Can Cluster and Discover Sparse Features. CoRR (2015)
Cengiz Pehlevan, Dmitri B. Chklovskii
Optimization theory of Hebbian/anti-Hebbian networks for PCA and whitening. Allerton (2015)
Cengiz Pehlevan, Tao Hu, Dmitri B. Chklovskii
A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data. CoRR (2015)
Cengiz Pehlevan, Dmitri B. Chklovskii
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks. NIPS (2015)
Tao Hu, Cengiz Pehlevan, Dmitri B. Chklovskii
A Hebbian/Anti-Hebbian Network for Online Sparse Dictionary Learning Derived from Symmetric Matrix Factorization. CoRR (2015)
Tao Hu, Dmitri B. Chklovskii
Online computation of sparse representations of time varying stimuli using a biologically motivated neural network. ICASSP (2015)
Cengiz Pehlevan, Tao Hu, Dmitri B. Chklovskii
A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data. Neural Comput. 27 (7) (2015)
Tao Hu, Cengiz Pehlevan, Dmitri B. Chklovskii
A Hebbian/Anti-Hebbian network for online sparse dictionary learning derived from symmetric matrix factorization. ACSSC (2014)
Cengiz Pehlevan, Dmitri B. Chklovskii
A Hebbian/Anti-Hebbian network derived from online non-negative matrix factorization can cluster and discover sparse features. ACSSC (2014)
Tao Hu, Dmitri B. Chklovskii
Sparse LMS via online linearized Bregman iteration. ICASSP (2014)
Juan Nunez-Iglesias, Ryan Kennedy, Toufiq Parag, Jianbo Shi, Dmitri B. Chklovskii
Machine learning of hierarchical clustering to segment n-dimensional images CoRR (2013)
Tao Hu, Zaid J. Towfic, Cengiz Pehlevan, Alex V. Genkin, Dmitri B. Chklovskii
A neuron as a signal processing device. ACSSC (2013)
Tao Hu, Juan Nunez-Iglesias, Shiv Naga Prasad Vitaladevuni, Lou Scheffer, Shan Xu, Mehdi Bolorizadeh, Harald F. Hess, Richard Fetter, Dmitri B. Chklovskii
Electron Microscopy Reconstruction of Brain Structure Using Sparse Representations Over Learned Dictionaries. IEEE Trans. Medical Imaging 32 (12) (2013)
Toufiq Parag, Victoria Butler, Dmitri B. Chklovskii
Tracking multiple neurons on worm images. Medical Imaging: Image Processing (2013)
Tao Hu, Dmitri B. Chklovskii
Online computation of sparse representations of time varying stimuli using a biologically motivated neural network CoRR (2012)
Dmitri B. Chklovskii, Daniel Soudry
"Neuronal spike generation mechanism as an oversampling, noise-shaping A-to-D converter". NIPS (2012)
Tao Hu, Alexander Genkin, Dmitri B. Chklovskii
A Network of Spiking Neurons for Computing Sparse Representations in an Energy-Efficient Way. Neural Comput. 24 (11) (2012)
Karol Gregor, Dmitri B. Chklovskii
A lattice filter model of the visual pathway. NIPS (2012)
Tao Hu, Juan Nunez-Iglesias, Shiv Naga Prasad Vitaladevuni, Lou Scheffer, Shan Xu, Mehdi Bolorizadeh, Harald F. Hess, Richard Fetter, Dmitri B. Chklovskii
Super-resolution using Sparse Representations over Learned Dictionaries: Reconstruction of Brain Structure using Electron Microscopy. CoRR (2012)
Tao Hu, Dmitri B. Chklovskii
Sparse LMS via Online Linearized Bregman Iteration CoRR (2012)
Shaul Druckmann, Tao Hu, Dmitri B. Chklovskii
A mechanistic model of early sensory processing based on subtracting sparse representations. NIPS (2012)
Tao Hu, Alexander Genkin, Dmitri B. Chklovskii
A network of spiking neurons for computing sparse representations in an energy efficient way CoRR (2012)
Tao Hu, Dmitri B. Chklovskii
Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME) CoRR (2012)
Lav R. Varshney, Beth L. Chen, Eric Paniagua, David H. Hall, Dmitri B. Chklovskii
Neuronal Network. PLoS Comput. Biol. 7 (2) (2011)
Daniel Glasner, Tao Hu, Juan Nunez-Iglesias, Lou Scheffer, Shan Xu, Harald F. Hess, Richard Fetter, Dmitri B. Chklovskii, Ronen Basri
High Resolution Segmentation of Neuronal Tissues from Low Depth-Resolution EM Imagery. EMMCVPR (2011)
Ashok Veeraraghavan, Alex V. Genkin, Shiv Naga Prasad Vitaladevuni, Lou Scheffer, Shan Xu, Harald F. Hess, Richard Fetter, Marco Cantoni, Graham Knott, Dmitri B. Chklovskii
Increasing depth resolution of electron microscopy of neural circuits using sparse tomographic reconstruction. CVPR (2010)
Shaul Druckmann, Dmitri B. Chklovskii
Over-complete representations on recurrent neural networks can support persistent percepts. NIPS (2010)
Tao Hu, Anthony M. Leonardo, Dmitri B. Chklovskii
Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME). NIPS (2009)
Beth L. Chen, Dmitri B. Chklovskii
Placement and routing optimization in the brain. ISPD (2006)
Quan Wen, Dmitri B. Chklovskii
Segregation of the Brain into Gray and White Matter: A Design Minimizing Conduction Delays. PLoS Comput. Biol. 1 (7) (2005)
Dmitri B. Chklovskii
Evolution as the blind engineer: wiring minimization in the brain. SLIP (2004)
Orit Shefi, Amir Harel, Dmitri B. Chklovskii, Eshel Ben-Jacob, Amir Ayali
Biophysical constraints on neuronal branching. Neurocomputing (2004)
Armen Stepanyants, Gábor Tamás, Dmitri B. Chklovskii
Are spatial positions of dendritic and axonal branches correlated or independent? Neurocomputing (2004)
Dmitri B. Chklovskii
Exact Solution for the Optimal Neuronal Layout Problem. Neural Comput. 16 (10) (2004)
Alexei A. Koulakov, Dmitri B. Chklovskii
Direction of motion maps in the visual cortex: a wire length minimization approach. Neurocomputing (2002)
Armen Stepanyants, Patrick R. Hof, Dmitri B. Chklovskii
Information storage capacity of synaptic connectivity patterns. Neurocomputing (2002)
Dmitri B. Chklovskii, Armen Stepanyants
Branching Law for Axons. NIPS (2002)
Dmitri B. Chklovskii
Optimal Sizes of Dendritic and Axonal Arbors. NIPS (1999)
Dmitri B. Chklovskii, Alexei A. Koulakov
Ocular dominance patterns in mammalian visual cortex: A wire length minimization approach CoRR (1999)

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Publication Activity (10 Years)

Top Topics

Top Venues

Dmitri B. Chklovskii