
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


Seth Lloyd - Quantum polar decomposition - IPAM at UCLA

Ewin Tang - On quantum linear algebra for machine learning - IPAM at UCLA

Jarrod McClean - Dequantization and quantum advantage in learning from experiments - IPAM at UCLA

Iordanis Kerenidis - New results in quantum linear algebra - IPAM at UCLA

Rolando Somma - The Quantum Linear Systems Problem - IPAM at UCLA

Yulong Dong - Fast algorithms for quantum signal processing - IPAM at UCLA

Dan Stamper-Kurn - Approaches to quantum information processing with cold atoms - IPAM at UCLA

Andras Gilyen - Quantum Algorithms for Quantum Information Processing Tasks - IPAM at UCLA

Di Fang - Time-dependent Hamiltonian Simulation of Highly Oscillatory Dynamics - IPAM at UCLA

Andrew Childs - Efficient quantum algorithm for dissipative nonlinear differential equations

Frank Wuerthwein - Global Cyberinfrastructure for LIGO, Virgo, Kagra, IceCube, and others

Jonathan Gair - Rapid and robust parameter estimation for gravitational wave observations

Patrick Godwin - Low-latency Noise Mitigation Techniques in GW Detector Data Using Aux Sensor Info

Kelly Holley-Bockelmann - Maximizing Multi-messenger Astronomy with LISA - IPAM at UCLA

Gabriele Vajente - Machine Learning and Gravitational Wave Detectors - IPAM at UCLA

Jess McIver - Rapid glitch mitigation for near-future gravitational-wave detectors - IPAM at UCLA

John Veitch - Computational Challenges in Gravitational Wave Parameter Estimation - IPAM at UCLA

Nathan Whitehorn - Neutrino in a haystack: computational challenges for IceCube Neutrino Observatory

Jenne Driggers - Improving the sensitivity of gravitational wave interferometers - IPAM at UCLA
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