Simons Foundation

Publications

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

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

G. Viejo, Sofia Skromne Carrasco, Adrien Peyrache

Learning a distance measure from the information-estimation geometry of data

G. Ohayon, P. Fiquet, F. Guth, Jona Ballé, E. P. Simoncelli

Emergent Manifold Separability during Reasoning in Large Language Models

Alexandre Polo, C. Chun, S. Chung

Months-long stability of the head-direction system

Sofia Skromne Carrasco, G. Viejo, Adrien Peyrache

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