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Institute for Pure & Applied Mathematics (IPAM) · Science

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

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Guillermo Valdes - Acoustic noise in gravitational-wave detectors - IPAM at UCLA

01 Dec 2021
30m
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Irene Di Palma - Deep learning algorithm for core-collapse supernova detection

01 Dec 2021
37m
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Josh Willis - Meeting the Computational Challenges of Third-Generation Gravitational-Wave Detectors

01 Dec 2021
45m
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Marco Cavaglia - Think out of the (counting) box - IPAM at UCLA

30 Nov 2021
50m
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Agata Trovato - Neural networks for gravitational-wave trigger selection in single-detector periods

30 Nov 2021
23m
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Michael Coughlin - Machine Learning in Multi-Messenger Era: Inference aaS & light curve augmentation

30 Nov 2021
45m
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Alejandro Torres-Forné - Variational models and algorithms for GW denoising and reconstruction

30 Nov 2021
39m
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Gabriela Gonzalez - Non-astrophysical transients in LIGO detectors: help with machine learning

29 Nov 2021
34m
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Ik Siong Heng - Gaussian Mixture Models for transient gravitational wave detection - IPAM at UCLA

29 Nov 2021
50m
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Joseph Bayley - Rapidly searching for continuous gravitational waves - IPAM at UCLA

29 Nov 2021
30m
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Deep Chatterjee - Machine learning in low-latency electromagnetic counterpart inference

29 Nov 2021
36m
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Ben Farr - Nobody Likes a Glitch - IPAM at UCLA

19 Nov 2021
31m
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Sylvia Biscoveanu - Power Spectral Density Uncertainty and Gravitational-Wave Parameter Estimation

19 Nov 2021
45m
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Rossella Gamba - Waveform systematics in the gravitational-wave inference of tidal parameters

19 Nov 2021
45m
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Geraint Pratten - Waveform Systematics and Binary Black Holes - IPAM at UCLA

19 Nov 2021
49m
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Patricia Schmidt - Introduction to Systematics - IPAM at UCLA

19 Nov 2021
7m
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Ling Sun - Tracking a continuous gravitational-wave signal with a hidden Markov model - IPAM at UCLA

19 Nov 2021
42m
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Jose Antonio Font - Inference with core-collapse supernova waveforms - IPAM at UCLA

18 Nov 2021
43m
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Jocelyn Read - Gravitational-wave observations of neutron-star mergers - IPAM at UCLA

18 Nov 2021
41m
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Juan Calderon-Bustillo - Challenge of characterising high-mass compact mergers: the case of GW190521

18 Nov 2021
37m
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