About optimal loss function for training physics-informed neural networks under respecting causality

5 April 2023

Papers citing "About optimal loss function for training physics-informed neural networks under respecting causality"

7 / 7 papers shown

Title
Separable Physics-Informed Neural Networks for the solution of elasticity problems V. A. Es'kin Danil V. Davydov Julia V. Guréva Alexey O. Malkhanov Mikhail E. Smorkalov PINN AI4CE 27 2 0 24 Jan 2024
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries Zong-Yi Li Daniel Zhengyu Huang Burigede Liu Anima Anandkumar AI4CE 122 254 0 11 Jul 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 366 12,003 0 04 Mar 2022
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 255 4,796 0 24 Feb 2021
Transformers in Vision: A Survey Salman Khan Muzammal Naseer Munawar Hayat Syed Waqas Zamir Fahad Shahbaz Khan M. Shah ViT 227 2,431 0 04 Jan 2021
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 183 760 0 13 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 128 509 0 11 Mar 2020