Fall 2022 Schedule

9/7:
Virtual
(Host:Lin/Di)
Mo Zhou, Duke University
Neural network approaches for high dimensional problems
9/14:
in-person
(Host:Michael)
Krutika Tawri, University of California, Berkeley
On stochastic partial differential equations with a Ladyzenskaya-Smagorinsky type nonlinearity
9/21:
Virtual
(Host:Di)
Li Wang, University of Minnesota
Variational methods for gradient flow
9/28:
Virtual
(Host:Di)
Felix Leditzky, UIUC
The platypus of the quantum channel zoo
10/5:
in-person
(Host:Lin)
Chao Ma, Stanford University
Implicit bias of optimization algorithms for neural networks and their effects on generalization
10/12:
in-person
(Host:Michael)
Mark Fornace, Caltech
Theoretical methods for nucleic acid secondary structure thermodynamics and kinetics
10/19:
in-person
(Host:Di)
Li Gao, University of Houston
Logarithmic Sobolev inequalities for matrices and matrix-valued functions
10/24:
4:10PM-5PM in-person. Note the special date!
(Host:Lin)
Matthew Colbrook, University of Cambridge
Residual Dynamic Mode Decomposition: Rigorous Data-Driven Computation of Spectral Properties of Koopman Operators for Dynamical Systems
11/2:
in-person
(Host:Di)
Yonah BornsWeil, University of California, Berkeley
Observable Trotter error bounds in the semiclassical regime
11/9:
in-person
(Host:Franziska)
Samuel Lanthaler, Caltech
Supervised learning in function space
11/16:
in-person
(Host:Franziska)
Lucas Bouck, University of Maryland
Finite Element Approximation of a Membrane Model for Liquid Crystal Polymeric Networks
11/23:No seminar. Happy Thanksgiving!
11/30:
in-person
(Host:Di)
Sui Tang, UCSB
Bridging the interacting particle models and data science via Gaussian process