
Institute for Pure & Applied Mathematics (IPAM)
The Institute for Pure and Applied Mathematics (IPAM) is a National Science Foundation Math Institute at the University of California, Los Angeles (UCLA) that fosters the interaction of mathematics with a broad range of science and technology, builds new interdisciplinary research communities, promotes mathematical innovation, and engages and transforms the world through mathematics. IPAM fulfills its mission through workshops and programs that connect mathematics and other disciplines or multiple areas of mathematics. These activities bring in thousands of visitors annually from academia, government, and industry. The NSF has encouraged IPAM to make the scientific presentations of our speakers available to a wider audience. While this YouTube channel contains many of our most popular videos, our full video archive is available at www.ipam.ucla.edu/videos.
Episodes


Ian Le - Cluster Algebras and Legendrian Knots - IPAM at UCLA

Nathan Geer - Non-Semisimple Skien TQFTs - IPAM at UCLA

Giulio Belletti - Introduction to quantum invariants - IPAM at UCLA

Michael Willis - Defining skein lasagna modules, and basic properties - IPAM at UCLA

Daniel Douglas - Introduction to the theory of Fock and Goncharov - IPAM at UCLA

Iordanis Romaidis - Contemporary Topics in Skein Theory - IPAM at UCLA

Jessica Purcell - Introduction to hyperbolic geometry - IPAM at UCLA

Melissa Zhang - Khovanov homology and generalizations - IPAM at UCLA

Ariana Chin - Introduction to Cluster Algebras - IPAM at UCLA

David Rose - Webs, foams, and invariants in low-dimensional topology - IPAM at UCLA

Lenny Ng - Introduction to Legendrian links and Lagrangian cobordisms - IPAM at UCLA

Shicheng Wang - A quick introduction to 3-manifolds - IPAM at UCLA

David Jordan - Introduction to skein theory - IPAM at UCLA

Numerical Algebraic Geometry & Correlated Electrons: Grassmannian, Response Function & Excited State

Takaharu Yaguchi - Geometric-Structure Machine Learning; Cross-System Prediction Hamiltonian Systems

Robert Joseph George - Verified Scientific Machine Learning in Lean - IPAM at UCLA

Matthew Sottile - Physics to Simulation: The Deep Stack of Formalization - IPAM at UCLA

Andrew Appel - Building a Formally Verified Finite Element Method Solver, One Component At a Time

Koji Hashimoto - On the interpretability of neural network solutions of PDEs in theoretical physics
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