APS March Meeting Abstracts

March 16, 2022

Join us at the APS March Meeting!

1. S. Qin, S. Farashahi, D. Lipshutz, A. M. Sengupta, D. B. Chklovskii, C. Pehlevan, Unveiling the dynamics and structure of drifting neural representations,  B03: Neural Systems I

2. A. Atanasov, B. Bordelon, C. Pehlevan, When are Neural Networks Kernel Learners?, F03: Physics of Learning II: Artificial systems

3. A. Canatar, B. Bordelon, C. Pehlevan, Statistical Mechanics of Kernel Regression and Wide Neural Networks, F09: Physics of Machine Learning I

4. J. Zavatone-Veth, A. Canatar, B. Ruben, C. Pehlevan, Non-Gaussian effects in finite Bayesian neural networks, F09: Physics of Machine Learning I

5. B. Bordelon, C. Pehlevan, Structured Neural Codes Enable Sample Ecient Learning Through Code-Task Alignment, K02: Neural Systems III

6. M. Farrell, B. Bordelon, S. Trivedi, C. Pehlevan, Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views?, K02: Neural Systems III