Coupling parameter and particle dynamics for adaptive sampling in Neural
Galerkin schemes

Coupling parameter and particle dynamics for adaptive sampling in Neural Galerkin schemes

27 June 2023

Yuxiao Wen

Eric Vanden-Eijnden

Benjamin Peherstorfer

Papers citing "Coupling parameter and particle dynamics for adaptive sampling in Neural Galerkin schemes"

8 / 8 papers shown

Title
Multi evolutional deep neural networks (Multi-EDNN) Hadden Kim T. Zaki 34 1 0 17 Jul 2024
Sequential-in-time training of nonlinear parametrizations for solving time-dependent partial differential equations Huan Zhang Yifan Chen Eric Vanden-Eijnden Benjamin Peherstorfer 28 2 0 01 Apr 2024
CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations Jules Berman Benjamin Peherstorfer 14 9 0 22 Feb 2024
Deep adaptive sampling for surrogate modeling without labeled data Xili Wang Keju Tang Jiayu Zhai Xiaoliang Wan Chao Yang 27 2 0 17 Feb 2024
Mitigating distribution shift in machine learning-augmented hybrid simulation Jiaxi Zhao Qianxiao Li 26 2 0 17 Jan 2024
Nonlinear embeddings for conserving Hamiltonians and other quantities with Neural Galerkin schemes Paul Schwerdtner Philipp Schulze Jules Berman Benjamin Peherstorfer 11 6 0 11 Oct 2023
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao B. Wen Qian Wang AAML 71 473 0 02 Feb 2021
Measuring Sample Quality with Kernels Jackson Gorham Lester W. Mackey 78 222 0 06 Mar 2017