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ORCIDDmitri B. Chklovskii
Dmitri "Mitya" Chklovskii
Person information
- affiliation: Simons Foundation
- affiliation: Howard Hughes Medical Institute, Janelia Farm Research Campus
- affiliation: Cold Spring Harbor Laboratory
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2020 – today
- 2026
[c44]Shanshan Qin, Joshua Pughe-Sanford, Alexander Genkin, Pembe Gizem Özdil, Philip Greengard, Anirvan M. Sengupta, Dmitri B. Chklovskii:
A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation. AAAI 2026: 2019-2028- 2025
- [c43]Joshua Pughe-Sanford, Xuehao Ding, Jason Moore, Anirvan M. Sengupta, Charles L. Epstein, Philip Greengard, Dmitri B. Chklovskii:
Neurons as Detectors of Coherent Sets in Sensory Dynamics. NeurIPS 2025 - 2024
- [i40]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 abs/2401.01489 (2024) - [i39]Siavash Golkar, Jules Berman, David Lipshutz, Robert Mihai Haret, Tim Gollisch, Dmitri B. Chklovskii:
Neuronal Temporal Filters as Normal Mode Extractors. CoRR abs/2401.03248 (2024) - 2023
- [j20]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) - [c42]Siavash Golkar, David Lipshutz, Tiberiu Tesileanu, Dmitri B. Chklovskii:
An Online Algorithm for Contrastive Principal Component Analysis. ICASSP 2023: 1-5 - [c41]David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii:
Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation. ICLR 2023 - [c40]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: 8902-8921 - [c39]Lyndon R. Duong, Eero P. Simoncelli, Dmitri B. Chklovskii, David Lipshutz:
Adaptive whitening with fast gain modulation and slow synaptic plasticity. NeurIPS 2023 - [i38]Lyndon R. Duong, David Lipshutz, David J. Heeger, Dmitri B. Chklovskii, Eero P. Simoncelli:
Statistical whitening of neural populations with gain-modulating interneurons. CoRR abs/2301.11955 (2023) - [i37]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 abs/2302.00545 (2023) - [i36]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 abs/2302.10051 (2023) - [i35]Yanis Bahroun, Shagesh Sridharan, Atithi Acharya, Dmitri B. Chklovskii, Anirvan M. Sengupta:
Unlocking the Potential of Similarity Matching: Scalability, Supervision and Pre-training. CoRR abs/2308.02427 (2023) - [i34]Lyndon R. Duong, Eero P. Simoncelli, Dmitri B. Chklovskii, David Lipshutz:
Adaptive whitening with fast gain modulation and slow synaptic plasticity. CoRR abs/2308.13633 (2023) - [i33]Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta:
Duality Principle and Biologically Plausible Learning: Connecting the Representer Theorem and Hebbian Learning. CoRR abs/2309.16687 (2023) - 2022
- [j19]David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii:
Biologically plausible single-layer networks for nonnegative independent component analysis. Biol. Cybern. 116(5): 557-568 (2022) - [j18]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): 891-938 (2022) - [c38]Jules Berman, Dmitri B. Chklovskii, Jingpeng Wu:
Bridging the Gap: Point Clouds for Merging Neurons in Connectomics. MIDL 2022: 150-159 - [c37]Alexander Genkin, David Lipshutz, Siavash Golkar, Tiberiu Tesileanu, Dmitri B. Chklovskii:
Biological Learning of Irreducible Representations of Commuting Transformations. NeurIPS 2022 - [c36]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 - [i32]David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii:
Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation. CoRR abs/2209.10634 (2022) - [i31]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 abs/2210.08340 (2022) - [i30]Siavash Golkar, David Lipshutz, Tiberiu Tesileanu, Dmitri B. Chklovskii:
An online algorithm for contrastive Principal Component Analysis. CoRR abs/2211.07723 (2022) - 2021
- [j17]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): 2309-2352 (2021) - [c35]Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta:
A Normative and Biologically Plausible Algorithm for Independent Component Analysis. NeurIPS 2021: 7368-7384 - [c34]Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii:
Neural optimal feedback control with local learning rules. NeurIPS 2021: 16358-16370 - [i29]Yanis Bahroun, Dmitri B. Chklovskii:
A Neural Network with Local Learning Rules for Minor Subspace Analysis. CoRR abs/2102.05501 (2021) - [i28]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 abs/2102.05503 (2021) - [i27]Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii:
Neural optimal feedback control with local learning rules. CoRR abs/2111.06920 (2021) - [i26]Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta:
A Normative and Biologically Plausible Algorithm for Independent Component Analysis. CoRR abs/2111.08858 (2021) - [i25]Jules Berman, Dmitri B. Chklovskii, Jingpeng Wu:
Bridging the Gap: Point Clouds for Merging Neurons in Connectomics. CoRR abs/2112.02039 (2021) - 2020
- [j16]Cengiz Pehlevan, Xinyuan Zhao, Anirvan M. Sengupta, Dmitri B. Chklovskii:
Neurons as Canonical Correlation Analyzers. Frontiers Comput. Neurosci. 14: 55 (2020) - [c33]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 - [c32]David Lipshutz, Charles Windolf, Siavash Golkar, Dmitri B. Chklovskii:
A Biologically Plausible Neural Network for Slow Feature Analysis. NeurIPS 2020 - [i24]David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii:
A biologically plausible neural network for multi-channel Canonical Correlation Analysis. CoRR abs/2010.00525 (2020) - [i23]David Lipshutz, Dmitri B. Chklovskii:
Bio-NICA: A biologically inspired single-layer network for Nonnegative Independent Component Analysis. CoRR abs/2010.12632 (2020) - [i22]David Lipshutz, Charlie Windolf, Siavash Golkar, Dmitri B. Chklovskii:
A biologically plausible neural network for Slow Feature Analysis. CoRR abs/2010.12644 (2020) - [i21]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 abs/2010.12660 (2020) - [i20]Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii:
A biologically plausible neural network for local supervision in cortical microcircuits. CoRR abs/2011.15031 (2020)
2010 – 2019
- 2019
- [j15]Cengiz Pehlevan, Dmitri B. Chklovskii:
Neuroscience-Inspired Online Unsupervised Learning Algorithms: Artificial neural networks. IEEE Signal Process. Mag. 36(6): 88-96 (2019) - [c31]Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii:
A Neural Network for Semi-supervised Learning on Manifolds. ICANN (1) 2019: 375-386 - [c30]Amirhossein Khalilian-Gourtani, Mariano Tepper, Victor Minden, Dmitri B. Chklovskii:
Strip the Stripes: Artifact Detection and Removal for Scanning Electron Microscopy Imaging. ICASSP 2019: 1060-1064 - [c29]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: 14178-14189 - [i19]Cengiz Pehlevan, Dmitri B. Chklovskii:
Neuroscience-inspired online unsupervised learning algorithms. CoRR abs/1908.01867 (2019) - [i18]Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii:
A Neural Network for Semi-Supervised Learning on Manifolds. CoRR abs/1908.08145 (2019) - 2018
- [j14]Mariano Tepper, Anirvan M. Sengupta, Dmitri B. Chklovskii:
Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling. J. Mach. Learn. Res. 19: 82:1-82:30 (2018) - [j13]Cengiz Pehlevan, Anirvan M. Sengupta, Dmitri B. Chklovskii:
Why Do Similarity Matching Objectives Lead to Hebbian/Anti-Hebbian Networks? Neural Comput. 30(1) (2018) - [c28]Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii:
Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics. ACSSC 2018: 104-111 - [c27]Andrea Giovannucci, Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii:
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching. IEEE BigData 2018: 1015-1022 - [c26]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: 7080-7090 - [i17]Andrea Giovannucci, Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii:
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching. CoRR abs/1808.02083 (2018) - 2017
- [j12]Cengiz Pehlevan, Sreyas Mohan, Dmitri B. Chklovskii:
Blind Nonnegative Source Separation Using Biological Neural Networks. Neural Comput. 29(11) (2017) - [c25]Cengiz Pehlevan, Alexander Genkin, Dmitri B. Chklovskii:
A clustering neural network model of insect olfaction. ACSSC 2017: 593-600 - [c24]Andrea Giovannucci, Johannes Friedrich, Matthew T. Kaufman, Anne Churchland, Dmitri B. Chklovskii, Liam Paninski, Eftychios A. Pnevmatikakis:
OnACID: Online Analysis of Calcium Imaging Data in Real Time. NIPS 2017: 2381-2391 - [i16]Cengiz Pehlevan, Anirvan M. Sengupta, Dmitri B. Chklovskii:
Adversarial synapses: Hebbian/anti-Hebbian learning optimizes min-max objectives. CoRR abs/1703.07914 (2017) - [i15]Cengiz Pehlevan, Sreyas Mohan, Dmitri B. Chklovskii:
Blind nonnegative source separation using biological neural networks. CoRR abs/1706.00382 (2017) - [i14]Mariano Tepper, Anirvan M. Sengupta, Dmitri B. Chklovskii:
The surprising secret identity of the semidefinite relaxation of K-means: manifold learning. CoRR abs/1706.06028 (2017) - 2016
- [c23]Yuansi Chen, Cengiz Pehlevan, Dmitri B. Chklovskii:
Self-calibrating neural networks for dimensionality reduction. ACSSC 2016: 1488-1495 - [c22]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: 1641-1645 - [i13]Yuansi Chen, Cengiz Pehlevan, Dmitri B. Chklovskii:
Self-calibrating Neural Networks for Dimensionality Reduction. CoRR abs/1612.03480 (2016) - 2015
- [j11]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): 1461-1495 (2015) - [j10]Arjun Bharioke, Dmitri B. Chklovskii:
Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit. PLoS Comput. Biol. 11(8) (2015) - [c21]Cengiz Pehlevan, Dmitri B. Chklovskii:
Optimization theory of Hebbian/anti-Hebbian networks for PCA and whitening. Allerton 2015: 1458-1465 - [c20]Tao Hu, Dmitri B. Chklovskii:
Online computation of sparse representations of time varying stimuli using a biologically motivated neural network. ICASSP 2015: 1991-1995 - [c19]Cengiz Pehlevan, Dmitri B. Chklovskii:
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks. NIPS 2015: 2269-2277 - [i12]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 abs/1503.00669 (2015) - [i11]Cengiz Pehlevan, Dmitri B. Chklovskii:
A Hebbian/Anti-Hebbian Network Derived from Online Non-Negative Matrix Factorization Can Cluster and Discover Sparse Features. CoRR abs/1503.00680 (2015) - [i10]Tao Hu, Cengiz Pehlevan, Dmitri B. Chklovskii:
A Hebbian/Anti-Hebbian Network for Online Sparse Dictionary Learning Derived from Symmetric Matrix Factorization. CoRR abs/1503.00690 (2015) - [i9]Cengiz Pehlevan, Dmitri B. Chklovskii:
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks. CoRR abs/1511.09426 (2015) - [i8]Cengiz Pehlevan, Dmitri B. Chklovskii:
Optimization theory of Hebbian/anti-Hebbian networks for PCA and whitening. CoRR abs/1511.09468 (2015) - 2014
- [c18]Tao Hu, Cengiz Pehlevan, Dmitri B. Chklovskii:
A Hebbian/Anti-Hebbian network for online sparse dictionary learning derived from symmetric matrix factorization. ACSSC 2014: 613-619 - [c17]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: 769-775 - [c16]Tao Hu, Dmitri B. Chklovskii:
Sparse LMS via online linearized Bregman iteration. ICASSP 2014: 7213-7217 - [r1]Arjun Bharioke, Louis K. Scheffer, Dmitri B. Chklovskii, Ian A. Meinertzhagen:
Drosophila Connectome. Encyclopedia of Computational Neuroscience 2014 - 2013
- [j9]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): 2179-2188 (2013) - [c15]Tao Hu, Zaid J. Towfic, Cengiz Pehlevan, Alex V. Genkin, Dmitri B. Chklovskii:
A neuron as a signal processing device. ACSSC 2013: 362-366 - [c14]Toufiq Parag, Victoria Butler, Dmitri B. Chklovskii:
Tracking multiple neurons on worm images. Image Processing 2013: 86692P - [i7]Juan Nunez-Iglesias, Ryan Kennedy, Toufiq Parag, Jianbo Shi, Dmitri B. Chklovskii:
Machine learning of hierarchical clustering to segment n-dimensional images. CoRR abs/1303.6163 (2013) - 2012
- [j8]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): 2852-2872 (2012) - [c13]Dmitri B. Chklovskii, Daniel Soudry:
"Neuronal spike generation mechanism as an oversampling, noise-shaping A-to-D converter". NIPS 2012: 512-520 - [c12]Karol Gregor, Dmitri B. Chklovskii:
A lattice filter model of the visual pathway. NIPS 2012: 1718-1726 - [c11]Shaul Druckmann, Tao Hu, Dmitri B. Chklovskii:
A mechanistic model of early sensory processing based on subtracting sparse representations. NIPS 2012: 1988-1996 - [i6]Tao Hu, Dmitri B. Chklovskii:
Sparse LMS via Online Linearized Bregman Iteration. CoRR abs/1210.0563 (2012) - [i5]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 abs/1210.0564 (2012) - [i4]Tao Hu, Alexander Genkin, Dmitri B. Chklovskii:
A network of spiking neurons for computing sparse representations in an energy efficient way. CoRR abs/1210.1530 (2012) - [i3]Tao Hu, Dmitri B. Chklovskii:
Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME). CoRR abs/1210.1544 (2012) - [i2]Tao Hu, Dmitri B. Chklovskii:
Online computation of sparse representations of time varying stimuli using a biologically motivated neural network. CoRR abs/1210.3741 (2012) - 2011
- [j7]Lav R. Varshney, Beth L. Chen, Eric Paniagua, David H. Hall, Dmitri B. Chklovskii:
Structural Properties of the Caenorhabditis elegans Neuronal Network. PLoS Comput. Biol. 7(2) (2011) - [c10]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: 261-272 - 2010
- [c9]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: 1767-1774 - [c8]Shaul Druckmann, Dmitri B. Chklovskii:
Over-complete representations on recurrent neural networks can support persistent percepts. NIPS 2010: 541-549
2000 – 2009
- 2009
- [c7]Tao Hu, Anthony M. Leonardo, Dmitri B. Chklovskii:
Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME). NIPS 2009: 790-798 - 2008
- [c6]Dmitri "Mitya" Chklovskii:
What can brain researchers learn from computer engineers and vice versa? ICCAD 2008: 2 - 2006
- [c5]Beth L. Chen, Dmitri B. Chklovskii:
Placement and routing optimization in the brain. ISPD 2006: 136-141 - 2005
- [j6]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) - 2004
- [j5]Armen Stepanyants, Gábor Tamás, Dmitri B. Chklovskii:
Are spatial positions of dendritic and axonal branches correlated or independent? Neurocomputing 58-60: 477-485 (2004) - [j4]Orit Shefi, Amir Harel, Dmitri B. Chklovskii, Eshel Ben-Jacob, Amir Ayali:
Biophysical constraints on neuronal branching. Neurocomputing 58-60: 487-495 (2004) - [j3]Dmitri B. Chklovskii:
Exact Solution for the Optimal Neuronal Layout Problem. Neural Comput. 16(10): 2067-2078 (2004) - [c4]Dmitri B. Chklovskii:
Evolution as the blind engineer: wiring minimization in the brain. SLIP 2004: 63 - 2002
- [j2]Alexei A. Koulakov, Dmitri B. Chklovskii:
Direction of motion maps in the visual cortex: a wire length minimization approach. Neurocomputing 44-46: 489-494 (2002) - [j1]Armen Stepanyants, Patrick R. Hof, Dmitri B. Chklovskii:
Information storage capacity of synaptic connectivity patterns. Neurocomputing 44-46: 661-665 (2002) - [c3]Dmitri B. Chklovskii, Armen Stepanyants:
Branching Law for Axons. NIPS 2002: 181-188
1990 – 1999
- 1999
- [c2]Dmitri B. Chklovskii, Charles F. Stevens:
Wiring Optimization in the Brain. NIPS 1999: 103-107 - [c1]Dmitri B. Chklovskii:
Optimal Sizes of Dendritic and Axonal Arbors. NIPS 1999: 108-114 - [i1]Dmitri B. Chklovskii, Alexei A. Koulakov:
Ocular dominance patterns in mammalian visual cortex: A wire length minimization approach. CoRR cond-mat/9906206 (1999)
Coauthor Index
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