Monday, March 31
Andrew Lewis (Queen's University)
Lecture 23 | Infinite-Dimensional Analysis and Differential Geometry
Professor Mike Stillman (Cornell University)
Lecture 10
Part of the Thematic Program in Commutative Algebra and Applications
Nikita Nikolaev, University of Birmingham
Resurgence of WKB Solutions for Schrödinger equations
Duncan Dauvergne (University of Toronto)
Characterizing the directed landscape through the KPZ fixed point
Tuesday, April 1
Rebecca R.G. (George Mason University)
Classifying neural ideals
Part of the Thematic Program in Commutative Algebra and Applications
Anibal Medina-Mardones (Western University)
Lecture 21 | Introduction to Topological Data Analysis
Rebecca R.G. (George Mason University)
Characteristic 0 closure operations
Part of the Thematic Program in Commutative Algebra and Applications
Kasra Rafi (University of Toronto)
Lecture 22 | Randomness in Groups
Wednesday, April 2
Andrew Lewis (Queen's University)
Lecture 24 | Infinite-Dimensional Analysis and Differential Geometry
Speakers:
John Griffiths (University of Toronto)
Jérémie Lefebvre (University of Ottawa)
Lecture 08: Effect of Noise in Neural Systems
Part of the Thematic Program on the Mathematics of Neuroscience
Maia Fraser (University of Ottawa)
Lecture 23 | Mathematical Introduction to Machine Learning
Thursday, April 3
Anibal Medina-Mardones (Western University)
Lecture 22 | Introduction to Topological Data Analysis
Eric Jovinelly, Brown University
Free Curves in Singular Varieties
Part of the Thematic Program in Commutative Algebra and Applications
Kasra Rafi (University of Toronto)
Lecture 23 | Randomness in Groups
Friday, April 4
Matthew Gerry, University of Toronto
Understanding multiple timescales in quantum dissipative dynamics
Masoud Ataei (University of Toronto)
Applications of Lehmer transform to Biological Signal Processing
Mark Poor, Cornell University
Some results about the pseudoarc and its homeomorphism group
Maia Fraser (University of Ottawa)
Lecture 24: Final Project Progress Meeting | Mathematical Introduction to Machine Learning (No Recording)