Applied Math

Organizers:  ryzhik [at] stanford.edu (Lenya Ryzhik) & lexing [at] stanford.edu (Lexing Ying)

For more information and access to abstracts, click here.

 

 

Past Events

Applied Math
Wednesday, December 6, 2023
12:00 PM
|
384H
Kirill Koroliev (Boston University)

In growing populations, the fate of mutations depends on their competitive ability against the ancestor and their ability to colonize new territory. I will discuss a theory that integrates both aspects fitness via a coupling between two classic reaction-diffusion equations: the KPZ equation,…

Applied Math
Wednesday, November 29, 2023
12:30 PM
|
384H
Jonathan Mattingly (Duke)

We consider the advection-diffusion equation on T^2 with a Lipschitz and time-periodic velocity field that alternates between two piecewise linear shear flows. We prove enhanced dissipation on the timescale |logν|, where ν is the diffusivity parameter. This is the optimal decay rate as ν→0 for…

Applied Math
Wednesday, November 15, 2023
12:00 PM
|
384H
Wotao Yin (Alibaba Inc)

This presentation focuses on the connection between GNNs (Graph Neural Networks) and mathematical optimization. We have recently found that, by defining an LP (Linear Programming) on a specific graph, GNNs can determine the feasibility of the LP problem and solve it with any desired…

Applied Math
Wednesday, November 8, 2023
12:00 PM
|
384H
Haoya Li (Stanford)

 Quantum phase estimation (QPE) is of essential importance in the field of quantum computing, serving as a foundational component of many quantum algorithms. This presentation will delve into the latest advancements that have been made to enhance the efficiency and practicality of QPE. We…

Applied Math
Wednesday, November 1, 2023
12:00 PM
|
384H
Tselil Schramm (Stanford)

Approximate message passing (AMP) is a family of iterative algorithms that are known to optimally solve many high-dimensional statistics optimization problems. In this talk, I will explain how to simulate a broad class of AMP algorithms in polynomial time using “local statistics hierarchy”…

Applied Math
Wednesday, October 25, 2023
12:00 PM
|
384H
Andre Nachbin (WPI)

We have deduced a weakly nonlinear, weakly dispersive Boussinesq system for water waves on a 1D branching channel, namely on a graph. The reduced model requires a  compatibility condition at the graph’s node, where the main reach bifurcates into two reaches. Our new nonlinear compatibility…

Applied Math
Wednesday, October 18, 2023
12:00 PM
|
384H
Cole Graham (Brown)

The world teems with examples of invasion, in which one steady state spatially invades another. Invasion can even display a universal character: fine details recur in seemingly unrelated systems. Reaction-diffusion equations provide a mathematical framework for these phenomena. In this talk, I…

Applied Math
Wednesday, September 27, 2023
12:00 PM
|
384H
Mark Alber (UC Riverside)

Abstract:

While blood clot formation has been relatively well studied, little is known about the mechanisms underlying the subsequent structural and mechanical clot remodeling called contraction or retraction. Impairment of the clot contraction process is associated with both life-…

Applied Math
Wednesday, June 7, 2023
12:00 PM
|
384H
Yuri Baktin (NYU)

For several classes of models (continuous space polymer models in
positive and zero temperature, HJB equations in dynamic environments),
we show that the shape function (also known as the effective
Lagrangian in the homogenization context) is differentiable and give a
formula for…

Applied Math
Wednesday, May 24, 2023
3:00 PM
|
384H
Dongbin Xiu (Ohio State University)

We present a framework of predictive modeling of unknown system from measurement data. The method is designed to discover/approximate the unknown evolution operator, i.e., flow map, behind the data. Deep neural network (DNN) is employed to construct such an approximation. Once an accurate DNN…