Elliptic PDE learning is provably data-efficient

Abstract: Can one learn a solution operator associated with a differential operator from pairs of solutions and righthand sides? If so, how many pairs are required? These two questions have received significant research attention in operator learning. More precisely, given input-output pairs from an unknown elliptic PDE, we will derive a theoretically rigorous scheme for learning the associated...

报告人：Alex Townsend (Cornell University)

From Coxeter-Conway friezes to cluster algebras

 

报告人：Bernhard Keller (Université Paris Cité)

Inverse Lax-Wendroff Procedure for Numerical Boundary Conditions

Abstract: When solving partial differential equations, finite difference methods have the advantage of simplicity, however they are usually only designed on Cartesian meshes. In this talk, we will discuss a class of high order finite difference numerical boundary condition for solving hyperbolic Hamilton-Jacobi equations, hyperbolic conservation laws, and convection-diffusion equations on comp...

报告人：Chi-Wang Shu (Brown University)

TBA

Click the link to join the Tencent meeting: https://meeting.tencent.com/dm/7PAPRVcnBhLkAbstract: TBABio：Felix Otto is director at the Max Planck Institute for Mathematics in the Sciences in Leipzig (Germany) since 2010. Before, he has been a professor at the University of California at Santa Barbara and at the Department of Applied Mathematics at the University of Bonn where he was the Managin...

报告人：Felix Otto

Benchmark-Tight Approximation Ratio of Simple Mechanism for a Unit-Demand Buyer

Abstract: We study revenue maximization in the unit-demand single-buyer setting. Our main result is that {\sf Uniform-Ironed-Virtual-Value Item Pricing} guarantees a {\em tight} $3$-approximation to the {\sf Duality Relaxation Benchmark} [Chawla-Malec-Sivan, EC'10/GEB'15; Cai-Devanur-Weinberg, STOC'16/ SICOMP'21], breaking the barrier of $4$ since [Chawla-Hartline-Malec-Sivan, STOC'10; Chawla-M...

报告人：Yaonan Jin (Huawei TCS Lab)