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Oliver Eberle - Interpretability for Deep Learning: Theory, Applications and Scientific Insights
Presenter
- Oliver Eberle
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
Shaowei Lin - Singular Learning, Relative Information and the Dual Numbers - IPAM at UCLA
Presenter
- Shaowei Lin
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
Blake Bordelon - Infinite limits and scaling laws of neural networks - IPAM at UCLA
Presenter
- Blake Bordelon
October 16, 2024
IPAM
Cengiz Pehlevan - 2 stories in mechanistic interpretation of natural & artificial neural computation
Presenter
- Cengiz Pehlevan
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
Elvis Dohmatob - The Mathematics of Scaling Laws and Model Collapse in AI - IPAM at UCLA
Presenter
- Elvis Dohmatob
October 14, 2024
IPAM
James Evans - Diversity, Disconnection, Discord, and Other Properties of Collective Intelligence
Presenter
- James Evans
September 27, 2024
IPAM
Natalia Velez - Games as a window into large-scale social phenomena - IPAM at UCLA
Presenter
- Natalia Velez
September 27, 2024
IPAM
Joel Leibo - Studying the behavior of generative AI-based agents in multi-agent systems
Presenter
- Joel Leibo
September 26, 2024
IPAM