Playlist: 31 videos

Dynamics and Discretization: PDEs, Sampling, and Optimization

0:43:36

Continuous Time Stochastic Gradient Descent and Flat Minimum Selection

Stephan Wojtowytsch (Texas A&M)
https://simons.berkeley.edu/talks/continuous-time-stochastic-gradient-descent-and-flat-minimum-selection
Dynamics and Discretization: PDEs, Sampling, and Optimization
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0:49:56

Consensus Based Sampling

Franca Hoffmann (University of Bonn)
https://simons.berkeley.edu/talks/consensus-based-sampling
Dynamics and Discretization: PDEs, Sampling, and Optimization
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0:29:55

Sampling From Wasserstein Barycenter

Thibaut Le Gouic (Ecole Centrale de Marseille)
https://simons.berkeley.edu/talks/sampling-wasserstein-barycenter
Dynamics and Discretization: PDEs, Sampling, and Optimization
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0:46:26

Extending the JKO Scheme Beyond Wasserstein-2 Gradient Flows

Matthew Jacobs (UCLA)
https://simons.berkeley.edu/talks/extending-jko-scheme-beyond-wasserstein-2-gradient-flows
Dynamics and Discretization: PDEs, Sampling, and Optimization
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0:47:6

Deterministic Particle Approximation for Nonlocal Transport Equations

Emanuela Radici (École Polytechnique Fédérale de Lausanne)
https://simons.berkeley.edu/talks/deterministic-particle-approximation-nonlocal-transport-equations
Dynamics and Discretization: PDEs, Sampling, and Optimization
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0:35:25

A Particle Method for Degenerate Diffusion, and Applications to Robotic Swarming

Olga Turanova (Michigan State University)
https://simons.berkeley.edu/talks/particle-method-degenerate-diffusion-and-applications-robotic-swarming
Dynamics and Discretization: PDEs, Sampling, and Optimization
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0:49:11

How to Train Better: Exploiting the Separability of DNNs

Lars Ruthotto (Emory University) and Elizabeth Newman (Emory University)
https://simons.berkeley.edu/talks/how-train-better-exploiting-separability-dnns
Dynamics and Discretization: PDEs, Sampling, and Optimization
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0:33:40

Mirror Descent Algorithms for Minimizing Interacting Free Energy

Lexing Ying (Stanford University)
https://simons.berkeley.edu/talks/mirror-descent-algorithms-minimizing-interacting-free-energy
Dynamics and Discretization: PDEs, Sampling, and Optimization
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0:31:15

Learning Interaction Kernels in Stochastic Systems of Interacting Particles from Multiple Trajectories

Jan Stanczuk (University of Cambridge)
https://simons.berkeley.edu/talks/learning-interaction-kernels-stochastic-systems-interacting-particles-multiple-trajectories
Dynamics and Discretization: PDEs, Sampling, and Optimization
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0:30:55

Discrete-To-Continuum Limits of Dynamical Optimal Transport Problems

Lorenzo Portinale (Hausdorff Center of Mathematics, Bonn)
https://simons.berkeley.edu/talks/discrete-continuum-limits-dynamical-optimal-transport-problems
Dynamics and Discretization: PDEs, Sampling, and Optimization
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