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Oliver Eberle - Interpretability for Deep Learning: Theory, Applications and Scientific Insights
Presenter
- Oliver Eberle
October 17, 2024
IPAM
Gintare Karolina Dziugaite - The dynamics of memorization and generalization in deep learning
Presenter
- Gintare Karolina Dziugaite
October 15, 2024
IPAM
Vidya Muthukumar - Comparison and transfer between tasks in overparameterized learning
Presenter
- Vidya Muthukumar
October 15, 2024
IPAM
Leena Vankadara - Scaling Insights from Infinite-Width Theory for Next Gen Architecture & Learning
Presenter
- Leena Vankadara
October 18, 2024
IPAM
Shaowei Lin - Singular Learning, Relative Information and the Dual Numbers - IPAM at UCLA
Presenter
- Shaowei Lin
October 16, 2024
IPAM
Blake Bordelon - Infinite limits and scaling laws of neural networks - IPAM at UCLA
Presenter
- Blake Bordelon
October 16, 2024
IPAM
Elvis Dohmatob - The Mathematics of Scaling Laws and Model Collapse in AI - IPAM at UCLA
Presenter
- Elvis Dohmatob
October 14, 2024
IPAM
Paul Riechers - geometric representation of far future in deep neural networks trained on next-token
Presenter
- Paul Riechers
October 16, 2024
IPAM
Mayank Mehta - Dynamics of brain's deep network - IPAM at UCLA
Presenter
- Mayank Mehta
October 17, 2024
IPAM
Nikos Tsilivis - The Price of Implicit Bias in Robust ML - IPAM at UCLA
Presenter
- Nikos Tsilivis
October 14, 2024
IPAM
Dmitry Krotov - Generative AI models through the lens of Dense Associative Memory - IPAM at UCLA
Presenter
- Dmitry Krotov
October 17, 2024
IPAM
Fanny Yang - Surprising phenomena of max-lp-margin classifiers in high dimensions - IPAM at UCLA
Presenter
- Fanny Yang
October 17, 2024
IPAM