Monday, September 28
Yevgeny Liokumovich (University of Toronto)
Lecture 05 | Mathematics for AI Safety
Noam Levi, EPFL - Swiss Federal Technology Institute of Lausanne
Internal Data Repetition Destroys Language Model Scaling Laws
Speakers:
Arul Shankar (University of Toronto)
Kevin Wilson (Borealis AI)
Lecture 03 | Elements of Mathematical Formalization and Auto-Formalization with Lean
Victor Ginsburg (University of California Berkeley)
Temperature chaos in polymers
Tuesday, September 29
Dario Poletti, Singapore University of Technology and Design (SUTD)
Aspects of thermalization and of emergence in non-equilibrium in many-body quantum systems
Chiaki Hara (Kyoto University)
Shareholder Engagement in an ESG-CAPM with Incomplete Markets: Much ado about nothing?
Wednesday, September 30
Yevgeny Liokumovich (University of Toronto)
Lecture 06 | Mathematics for AI Safety
Thursday, October 1
Mark Iwen, Michigan State University
Sparse Spectral Methods for Solving High-Dimensional and Multiscale PDEs
Andrii Bobrov (Kyiv Academic University)
On the Monge and Beckmann Formulations of Optimal Transport in Abstract Wiener Spaces
Part of the Thematic Program on Optimal Transport in Natural Sciences and Statistics
Friday, October 2
Zohar Ringel (The Hebrew University of Jerusalem)
Lecture 01 | Mini-Course on Statistical Mechanical Approaches to Deep Learning
Andy Zucker, University of Waterloo
Big Ramsey degrees for infinitely constrained binary free amalgamation classes.
Daniel Kunin, University of California, Berkeley
Gradients, Groups, Grids: How neural networks learn features in algebraic tasks
