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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
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
Paul Riechers - geometric representation of far future in deep neural networks trained on next-token
Presenter
- Paul Riechers
October 16, 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
Patrick Shafto - Common Ground in Cooperative Communication - IPAM at UCLA
Presenter
- Patrick Shafto
October 15, 2024
IPAM
Boris Hanin - Neural Network Scaling Limits - IPAM at UCLA
Presenter
- Boris Hanin
October 14, 2024
IPAM
Wu Lin - A framework for designing (non-diagonal) adaptive training methods - IPAM at UCLA
Presenter
- Wu Lin
October 14, 2024
IPAM
Elvis Dohmatob - The Mathematics of Scaling Laws and Model Collapse in AI - IPAM at UCLA
Presenter
- Elvis Dohmatob
October 14, 2024
IPAM