Videos

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Integrating Autonomous Systems for Advanced Material Discovery: Bridging Experiments and Theory Through Optimized Rewards Thumbnail

Integrating Autonomous Systems for Advanced Material Discovery: Bridging Experiments and Theory Through Optimized Rewards

Presenter
  • Sergei Kalinin
May 16, 2024
IMSI

Ceresa cycles of Fermat curves

Presenter
  • Payman Eskandari
May 15, 2024
ICERM

Archimedean heights of generalized Heegner cycles

Presenter
  • David Lilienfeldt
May 15, 2024
ICERM

Hyperelliptic curves mapping to abelian surfaces and applications to Beilinson's conjecture for 0-cycles

Presenter
  • Evangelia Gazaki
May 15, 2024
ICERM
Understanding and Mitigating Bias in Autonomous Materials Characterization and Discovery Thumbnail

Understanding and Mitigating Bias in Autonomous Materials Characterization and Discovery

Presenter
  • Jason Hattrick-Simpers
May 15, 2024
IMSI
Optimization, Sampling and Generative Modeling in Non-Euclidean Spaces Thumbnail

Optimization, Sampling and Generative Modeling in Non-Euclidean Spaces

Presenter
  • Molei Tao
May 15, 2024
IMSI
Learning dislocation dynamics with graph neural networks Thumbnail

Learning dislocation dynamics with graph neural networks

Presenter
  • Nicolas Bertin
May 15, 2024
IMSI
Descriptor coarse-graining and forecasting atomic simulations Thumbnail

Descriptor coarse-graining and forecasting atomic simulations

Presenter
  • Thomas Swinburne
May 15, 2024
IMSI
A Neural Network Approach to Learning Steady States and Their Stability of Parametric Dynamical Systems Thumbnail

A Neural Network Approach to Learning Steady States and Their Stability of Parametric Dynamical Systems

Presenter
  • Xiaochuan Tian
May 15, 2024
IMSI

Normal functions and Ceresa-like cycles

Presenter
  • Matt Kerr
May 14, 2024
ICERM
Resolution of the Kohayakawa--Kreuter Conjecture Thumbnail

Resolution of the Kohayakawa--Kreuter Conjecture

Presenter
  • Raphael Steiner
May 14, 2024
IAS
Fokker-Planck-based Inverse Reinforcement Learning — A Physics-Constrained Approach to Markov Decision Process Models of Cell Dynamics Thumbnail

Fokker-Planck-based Inverse Reinforcement Learning — A Physics-Constrained Approach to Markov Decision Process Models of Cell Dynamics

Presenter
  • Krishna Garikipati
May 14, 2024
IMSI