
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


Max Tegmark - Neural network interpretability: symmetry, geometry and formal verification

Bin Yu - Neural network interpretability: symmetry, geometry and formal verification

Josh Batson - Interpretability: From Art Towards Science - IPAM at UCLA

Marina Meila - Contrastive Explanations: a geometric and topological view - IPAM at UCLA

Paul Christiano - Mechanistic Estimation - IPAM at UCLA

Jacob Hilton - Miniature mathematical mysteries: uninterpreted models w/ fewer than 1,500 parameters

Been Kim - Changing Shapes: Interpretability, AI, and the Future of Human Agency - IPAM at UCLA

Miriam Kuzbary - 0-Surgeries on Links - IPAM at UCLA

Viktória Földvári - Maximal tb Representatives of Double Twist Knots - IPAM at UCLA

Yasemin Yildirim - Constructing and classifying Legendrian doubles - IPAM at UCLA

Tanushree Shah - Contact cosmetic surgery - IPAM at UCLA

Shancong Mou - Derivative-Informed Training of Neural Operators on the Fly - IPAM at UCLA

Simon Van Mulders - Model-aided TCV operation through routine pre-shot, real-time and post-shot...

Stephen Becker - Some new bi-fidelity methods for UQ and optimization - IPAM at UCLA

Sophia Henneberg - Optimization of Quasi-Axisymmetric Stellarator- ; Tokamak Hybrids - IPAM at UCLA

Andy Rothstein - AI-Driven Event Prediction and Fault-Resilient Plasma Control on DIII-D

Cory Hauck - Approximate entropy-based moment closures - IPAM at UCLA

Rebekah White - Surrogate-Based Optimization of Magnetized Liner Inertial Fusion Target Design

Yunan Yang - Adjoint Direct Simulation Monte Carlo for Optimization and Control of Rarefied Flows
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