Monday, October 19
Speaker:
Wilfrid Gangbo (University of California, Los Angeles)
Part of the Thematic Program on Optimal Transport in Natural Sciences and Statistics
Yevgeny Liokumovich (University of Toronto)
Lecture 09 | Mathematics for AI Safety
Anastasis Kratsios (McMaster University)
Lecture 14 | Mathematical Foundations of AI
Lionel Levine, Cornell University
Speakers:
Arul Shankar (University of Toronto)
Kevin Wilson (Borealis AI)
Lecture 05 | Elements of Mathematical Formalization and Auto-Formalization with Lean
Wilfrid Gangbo (University of California, Los Angeles)
Lecture 01: An Introduction to Quantum Marginal Problems
Part of the Thematic Program on Optimal Transport in Natural Sciences and Statistics
Tuesday, October 20
Part of the Thematic Program on Optimal Transport in Natural Sciences and Statistics
Ursula Martin (Oxford), Thomas Bloom (University of Manchester), Jarod Alper (University of Washington, Google Deepmind)
5) Affirm humanity of authorship and 6) Put effort in proper attribution
Wilfrid Gangbo (University of California, Los Angeles)
Lecture 02: From Classical Relaxation to Noncommutative Obstructions: An Introductory Overview
Part of the Thematic Program on Optimal Transport in Natural Sciences and Statistics
Wednesday, October 21
Part of the Thematic Program on Optimal Transport in Natural Sciences and Statistics
Yevgeny Liokumovich (University of Toronto)
Lecture 10 | Mathematics for AI Safety
Anastasis Kratsios (McMaster University)
Lecture 15 | Mathematical Foundations of AI
Wilfrid Gangbo (University of California, Los Angeles)
Lecture 03: Optimal transport and Mean Field Games on graphs
Part of the Thematic Program on Optimal Transport in Natural Sciences and Statistics
Thursday, October 22
Part of the Thematic Program on Optimal Transport in Natural Sciences and Statistics
Anastasis Kratsios (McMaster University)
Lecture 16 | Mathematical Foundations of AI
Friday, October 23
Part of the Thematic Program on Optimal Transport in Natural Sciences and Statistics
Zohar Ringel (The Hebrew University of Jerusalem)
Lecture 03 | Mini-Course on Statistical Mechanical Approaches to Deep Learning
Gurudev Dutt, University of Pittsburgh
Towards Macroscopic Superpositions with Levitated Diamond Crystals
Ding-Xuan Zhou, University of Sydney
Approximation and Learning Theory
Pourya Memarpanahi, University of Toronto
TBA
Dennis Zvigelsky, McMaster University
Model Theory & Machine Learning: A Web of Dimensions in Continuous Logic and the Regression Setting
