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Physics-informed neural networks for the shallow-water equations on the sphere

1 April 2021

Papers citing "Physics-informed neural networks for the shallow-water equations on the sphere"

22 / 22 papers shown

Title
When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization? Zheyuan Hu Ameya Dilip Jagtap George Karniadakis Kenji Kawaguchi AI4CE PINN 52 88 0 20 Sep 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 162 284 0 20 Apr 2021
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 141 914 0 28 Jul 2020
A generative adversarial network approach to (ensemble) weather prediction Alexander Bihlo AI4Cl 46 79 0 13 Jun 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 808 42,055 0 28 May 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
Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere Jonathan A. Weyn Dale Durran R. Caruana AI4Cl 41 262 0 15 Mar 2020
Ensemble methods for neural network-based weather forecasts S. Scher G. Messori 22 6 0 13 Feb 2020
Gradient Surgery for Multi-Task Learning Tianhe Yu Saurabh Kumar Abhishek Gupta Sergey Levine Karol Hausman Chelsea Finn 174 1,221 0 19 Jan 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks Sizhuang He Yujun Teng P. Perdikaris AI4CE PINN 97 295 0 13 Jan 2020
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs Xuhui Meng Zhen Li Dongkun Zhang George Karniadakis PINN AI4CE 77 453 0 23 Sep 2019
Lookahead Optimizer: k steps forward, 1 step back Michael Ruogu Zhang James Lucas Geoffrey E. Hinton Jimmy Ba ODL 145 730 0 19 Jul 2019
Precipitation nowcasting using a stochastic variational frame predictor with learned prior distribution Alexander Bihlo BDL 43 10 0 13 May 2019
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks Georgios Kissas Yibo Yang E. Hwuang W. Witschey John A. Detre P. Perdikaris AI4CE 123 373 0 13 May 2019
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes Yang You Jing Li Sashank J. Reddi Jonathan Hseu Sanjiv Kumar Srinadh Bhojanapalli Xiaodan Song J. Demmel Kurt Keutzer Cho-Jui Hsieh ODL 238 996 0 01 Apr 2019
Multi-Task Learning as Multi-Objective Optimization Ozan Sener V. Koltun 163 1,283 0 10 Oct 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 154 1,451 0 22 Jun 2018
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 775 36,813 0 25 Aug 2016
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 566 7,992 0 13 Jun 2015
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 166 2,808 0 20 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,115 0 22 Dec 2014
Playing Atari with Deep Reinforcement Learning Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra Martin Riedmiller 127 12,231 0 19 Dec 2013