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Adityanarayanan Radhakrishnan - How do neural networks learn features from data? - IPAM at UCLA
Presenter
- Adityanarayanan Radhakrishnan
October 18, 2024
IPAM
Shaowei Lin - Singular Learning, Relative Information and the Dual Numbers - IPAM at UCLA
Presenter
- Shaowei Lin
October 16, 2024
IPAM
Paul Riechers - geometric representation of far future in deep neural networks trained on next-token
Presenter
- Paul Riechers
October 16, 2024
IPAM
Wu Lin - A framework for designing (non-diagonal) adaptive training methods - IPAM at UCLA
Presenter
- Wu Lin
October 14, 2024
IPAM
Lily Reeves - Distances in hierarchical percolation - IPAM at UCLA
Presenter
- Lily Reeves
May 9, 2024
IPAM
Yuval Peled - Sharp Threshold for Rigidity of Random Graphs - IPAM at UCLA
Presenter
- Yuval Peled
May 8, 2024
IPAM
Hariharan Narayanan - Sums of GUE matrices, concentration of hives, correlation decay of eigengaps
Presenter
- Hariharan Narayanan
April 17, 2024
IPAM
Tomas Berggren - Geometry of the doubly periodic Aztec dimer model - IPAM at UCLA
Presenter
- Tomas Berggren
March 25, 2024
IPAM
Thien Le - On the hardness of learning under symmetries - IPAM at UCLA
Presenter
- Thien Le
February 27, 2024
IPAM