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Zecheng Zhang - Deep Operator Learning Approximation and Distributed Applications - IPAM at UCLA
Presenter
- Zecheng Zhang
July 16, 2025
IPAM
Neural posterior estimation for gravitational-wave inference Continued
Presenter
- Stephen Green
June 4, 2025
ICERM
Neural posterior estimation for gravitational-wave inference
Presenter
- Stephen Green
June 4, 2025
ICERM
Robert Batterman - Deep Learning, Correlations, and the Statistics of Natural Images - IPAM at UCLA
Presenter
- Robert Batterman
November 22, 2024
IPAM
Adityanarayanan Radhakrishnan - How do neural networks learn features from data? - IPAM at UCLA
Presenter
- Adityanarayanan Radhakrishnan
October 18, 2024
IPAM
Leena Vankadara - Scaling Insights from Infinite-Width Theory for Next Gen Architecture & Learning
Presenter
- Leena Vankadara
October 18, 2024
IPAM
Misha Belkin - Emergence and grokking in "simple" architectures - IPAM at UCLA
Presenter
- Misha Belkin
October 18, 2024
IPAM
Dmitry Krotov - Generative AI models through the lens of Dense Associative Memory - IPAM at UCLA
Presenter
- Dmitry Krotov
October 17, 2024
IPAM
Oliver Eberle - Interpretability for Deep Learning: Theory, Applications and Scientific Insights
Presenter
- Oliver Eberle
October 17, 2024
IPAM
Mayank Mehta - Dynamics of brain's deep network - IPAM at UCLA
Presenter
- Mayank Mehta
October 17, 2024
IPAM
Mauro Maggioni - On exploiting compositional structure: one bit of theory and one application
Presenter
- Mauro Maggioni
October 17, 2024
IPAM
Dan Roy - Size of Teachers as Measure of Data Complexity: PAC-Bayes Excess Risk Bounds & Scaling Law
Presenter
- Dan Roy
October 16, 2024
IPAM