Learning Physics-Informed Neural Networks without Stacked
Back-propagation

Learning Physics-Informed Neural Networks without Stacked Back-propagation

18 February 2022

Jiang Bian

Papers citing "Learning Physics-Informed Neural Networks without Stacked Back-propagation"

7 / 7 papers shown

Title
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Zekun Shi Zheyuan Hu Min Lin Kenji Kawaguchi 383 8 0 27 Nov 2024
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 497 2,414 0 18 Oct 2020
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning Sijia Liu Pin-Yu Chen B. Kailkhura Gaoyuan Zhang A. Hero III P. Varshney 70 231 0 11 Jun 2020
On the convergence of physics informed neural networks for linear second-order elliptic and parabolic type PDEs Yeonjong Shin Jérome Darbon George Karniadakis PINN 62 79 0 03 Apr 2020
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius Runtian Zhai Chen Dan Di He Huan Zhang Boqing Gong Pradeep Ravikumar Cho-Jui Hsieh Liwei Wang OOD AAML 87 177 0 08 Jan 2020
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 150 2,039 0 08 Feb 2019
PDE-Net: Learning PDEs from Data Zichao Long Yiping Lu Xianzhong Ma Bin Dong DiffM AI4CE 43 756 0 26 Oct 2017