CCN: Publications

There Will Be a Scientific Theory of Deep Learning

Jamie Simon, Daniel Kunin, Alexander Atanasov, Enric Boix-Adser`, Blake Bordelon, J. Cohen, N. Ghosh, F. Guth, Arthur Jacot, Mason Kamb, Dhruva Karkada, Eric J. Michaud, Berkan Ottlik, Joseph Turnbull

Modulating Cross-Modal Convergence with Single-Stimulus, Intra-Modal Dispersion

Eghbal A. Hosseini, Brian Cheung, Evelina Fedorenko, A. Williams

Estimating Dimensionality of Neural Representations from Finite Samples

C. Chun, A. Canatar, S. Chung , Daniel Lee

Quasi Monte Carlo methods enable extremely low-dimensional deep generative models

Miles Martinez, A. Williams

Partial Soft-Matching Distance for Neural Representational Comparison with Partial Unit Correspondence

Chaitanya Kapoor, A. Williams, Meenakshi Khosla

A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation

S. Qin, J. Pughe-Sanford, A. Genkin, Pembe Gizem Ozdil, P. Greengard, A. Sengupta, D. Chklovskii

Linear Readout of Neural Manifolds with Continuous Variables

Will Slatton, C. Chou , S. Chung

Diagnosing Generalization Failures from Representational Geometry Markers

C. Chou , A. Kirsanov, Yao-Yuan Yang, S. Chung

Natural Image Statistics, Visual Representation, and Denoising

Imran Thobani, Alisa Leshchenko, E. P. Simoncelli

The head-direction signal is generated by multiple attractor-like networks

G. Viejo, Sofia Skromne Carrasco, Adrien Peyrache