Multi-Objective Loss Balancing for Physics-Informed Deep Learning

19 October 2021

Papers citing "Multi-Objective Loss Balancing for Physics-Informed Deep Learning"

40 / 40 papers shown

Title
Expert-elicitation method for non-parametric joint priors using normalizing flows F. Bockting Stefan T. Radev Paul-Christian Bürkner BDL 162 1 0 24 Nov 2024
Failure-informed adaptive sampling for PINNs Zhiwei Gao Liang Yan Tao Zhou 67 82 0 01 Oct 2022
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu Min Zhu Qinyan Tan Yadhu Kartha Lu Lu 60 371 0 21 Jul 2022
A novel meta-learning initialization method for physics-informed neural networks Xu Liu Xiaoya Zhang Wei Peng Weien Zhou Wen Yao AI4CE 55 74 0 23 Jul 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 142 281 0 20 Apr 2021
A Deep Collocation Method for the Bending Analysis of Kirchhoff Plate Hongwei Guo X. Zhuang Timon Rabczuk AI4CE 43 436 0 04 Feb 2021
A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder Youngkyu Kim Youngsoo Choi David Widemann T. Zohdi AI4CE 46 192 0 25 Sep 2020
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism L. McClenny U. Braga-Neto PINN 72 458 0 07 Sep 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 117 903 0 28 Jul 2020
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks Colby Wight Jia Zhao 61 223 0 09 Jul 2020
Implicit Neural Representations with Periodic Activation Functions Vincent Sitzmann Julien N. P. Martel Alexander W. Bergman David B. Lindell Gordon Wetzstein AI4TS 118 2,543 0 17 Jun 2020
Transfer learning based multi-fidelity physics informed deep neural network S. Chakraborty PINN OOD AI4CE 50 164 0 19 May 2020
Accelerating Physics-Informed Neural Network Training with Prior Dictionaries Wei Peng Weien Zhou Jun Zhang Wen Yao PINN AI4CE 94 31 0 17 Apr 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 163 530 0 11 Mar 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks Sizhuang He Yujun Teng P. Perdikaris AI4CE PINN 89 293 0 13 Jan 2020
Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity Nikolaos N. Vlassis R. Ma WaiChing Sun AI4CE 39 175 0 08 Jan 2020
SoftAdapt: Techniques for Adaptive Loss Weighting of Neural Networks with Multi-Part Loss Functions A. Heydari Craig Thompson A. Mehmood 48 61 0 27 Dec 2019
Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS Petro B. Liashchynskyi Pavlo Liashchynskyi 38 542 0 12 Dec 2019
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs Xuhui Meng Zhen Li Dongkun Zhang George Karniadakis PINN AI4CE 54 450 0 23 Sep 2019
Meta-Learning with Implicit Gradients Aravind Rajeswaran Chelsea Finn Sham Kakade Sergey Levine 94 854 0 10 Sep 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 95 1,521 0 10 Jul 2019
$Transfer learning enhanced physics informed neural network for phase-field modeling of fracture$ Transfer learning enhanced physics informed neural network for phase-field modeling of fracture S. Goswami C. Anitescu S. Chakraborty Timon Rabczuk PINN 61 607 0 04 Jul 2019
Multi-Task Learning as Multi-Objective Optimization Ozan Sener V. Koltun 132 1,275 0 10 Oct 2018
A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations Philipp Grohs F. Hornung Arnulf Jentzen Philippe von Wurstemberger 47 170 0 07 Sep 2018
Probabilistic Model-Agnostic Meta-Learning Chelsea Finn Kelvin Xu Sergey Levine BDL 255 670 0 07 Jun 2018
Group Normalization Yuxin Wu Kaiming He 190 3,644 0 22 Mar 2018
On First-Order Meta-Learning Algorithms Alex Nichol Joshua Achiam John Schulman 221 2,229 0 08 Mar 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations M. Raissi PINN AI4CE 108 753 0 20 Jan 2018
Theory of Deep Learning IIb: Optimization Properties of SGD Chiyuan Zhang Q. Liao Alexander Rakhlin Brando Miranda Noah Golowich T. Poggio ODL 44 71 0 07 Jan 2018
Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 67 612 0 28 Nov 2017
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks Zhao Chen Vijay Badrinarayanan Chen-Yu Lee Andrew Rabinovich ODL 136 1,282 0 07 Nov 2017
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm Chelsea Finn Sergey Levine SSL 86 223 0 31 Oct 2017
DGM: A deep learning algorithm for solving partial differential equations Justin A. Sirignano K. Spiliopoulos AI4CE 84 2,057 0 24 Aug 2017
Sobolev Training for Neural Networks Wojciech M. Czarnecki Simon Osindero Max Jaderberg G. Swirszcz Razvan Pascanu 51 244 0 15 Jun 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 591 130,942 0 12 Jun 2017
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics Alex Kendall Y. Gal R. Cipolla 3DH 246 3,114 0 19 May 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 798 11,866 0 09 Mar 2017
Why and When Can Deep -- but Not Shallow -- Networks Avoid the Curse of Dimensionality: a Review T. Poggio H. Mhaskar Lorenzo Rosasco Brando Miranda Q. Liao 97 578 0 02 Nov 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.3K 149,842 0 22 Dec 2014
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 317 7,923 0 13 Jun 2012