Multi-Objective Loss Balancing for Physics-Informed Deep Learning

19 October 2021

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

38 / 38 papers shown

Title
Physics Informed Constrained Learning of Dynamics from Static Data Pengtao Dang Tingbo Guo Melissa Fishel Guang Lin Wenzhuo Wu Sha Cao Chi Zhang PINN AI4CE 49 0 0 17 Apr 2025
Enabling Automatic Differentiation with Mollified Graph Neural Operators Ryan Y. Lin Julius Berner Valentin Duruisseaux David Pitt Daniel Leibovici Jean Kossaifi Kamyar Azizzadenesheli Anima Anandkumar AI4CE 36 0 0 11 Apr 2025
PINNverse: Accurate parameter estimation in differential equations from noisy data with constrained physics-informed neural networks Marius Almanstötter Roman Vetter Dagmar Iber PINN 27 1 0 07 Apr 2025
Expert-elicitation method for non-parametric joint priors using normalizing flows F. Bockting Stefan T. Radev Paul-Christian Burkner BDL 88 1 0 24 Nov 2024
Beyond Derivative Pathology of PINNs: Variable Splitting Strategy with Convergence Analysis Yesom Park Changhoon Song Myungjoo Kang 21 2 0 30 Sep 2024
Domain-decoupled Physics-informed Neural Networks with Closed-form Gradients for Fast Model Learning of Dynamical Systems Henrik Krauss Tim-Lukas Habich Max Bartholdt Thomas Seel Moritz Schappler PINN AI4CE 27 2 0 27 Aug 2024
Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold Networks Spyros Rigas M. Papachristou Theofilos Papadopoulos Fotios Anagnostopoulos Georgios Alexandridis AI4CE 34 21 0 24 Jul 2024
Spatio-temporal Attention-based Hidden Physics-informed Neural Network for Remaining Useful Life Prediction Feilong Jiang Xiaonan Hou Min Xia 19 1 0 20 May 2024
Discovering Physics-Informed Neural Networks Model for Solving Partial Differential Equations through Evolutionary Computation Bo Zhang Chao Yang PINN 22 3 0 18 May 2024
Physics-Guided Neural Networks for Intraventricular Vector Flow Mapping Han Ling Salomé Bru Julia Puig F. Vixège Simon Mendez Franck Nicoud P. Courand Olivier Bernard Damien Garcia 42 6 0 19 Mar 2024
Thermal Earth Model for the Conterminous United States Using an Interpolative Physics-Informed Graph Neural Network (InterPIGNN) M. Aljubran Roland N. Horne AI4CE 34 8 0 15 Mar 2024
Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes Tobias Würth Niklas Freymuth C. Zimmerling Gerhard Neumann Luise Kärger AI4CE 19 1 0 16 Feb 2024
Architectural Strategies for the optimization of Physics-Informed Neural Networks Hemanth Saratchandran Shin-Fang Chng Simon Lucey AI4CE 23 0 0 05 Feb 2024
An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations Valentin Duruisseaux Amit Chakraborty AI4CE 11 1 0 04 Nov 2023
Exact and soft boundary conditions in Physics-Informed Neural Networks for the Variable Coefficient Poisson equation Sebastian Barschkis 13 1 0 04 Oct 2023
On Training Derivative-Constrained Neural Networks KaiChieh Lo Daniel Huang 11 3 0 02 Oct 2023
Physics-informed neural networks modeling for systems with moving immersed boundaries: application to an unsteady flow past a plunging foil Rahul Sundar Dipanjan Majumdar Didier Lucor Sunetra Sarkar PINN AI4CE 25 6 0 23 Jun 2023
Learning CO $_2$ plume migration in faulted reservoirs with Graph Neural Networks X. Ju Franccois P. Hamon Gege Wen Rayan Kanfar Mauricio Araya-Polo H. Tchelepi AI4CE 16 1 0 16 Jun 2023
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs Zhongkai Hao J. Yao Chang Su Hang Su Ziao Wang ... Zeyu Xia Yichi Zhang Songming Liu Lu Lu Jun Zhu PINN 20 29 0 15 Jun 2023
NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training B.-L. Lu Christian Moya Guang Lin PINN 20 11 0 03 Mar 2023
Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains Ali Harandi Ahmad Moeineddin Michael Kaliske Stefanie Reese Shahed Rezaei AI4CE PINN 18 42 0 09 Feb 2023
Failure-informed adaptive sampling for PINNs, Part II: combining with re-sampling and subset simulation Zhi-Hao Gao Tao Tang Liang Yan Tao Zhou 17 18 0 03 Feb 2023
LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry Jian Cheng Wong P. Chiu C. Ooi M. Dao Yew-Soon Ong AI4CE PINN 13 10 0 03 Feb 2023
Deep learning for full-field ultrasonic characterization Yang Xu Fatemeh Pourahmadian Jian Song Congli Wang AI4CE 16 4 0 06 Jan 2023
Deep Learning and Computational Physics (Lecture Notes) Deep Ray Orazio Pinti Assad A. Oberai PINN AI4CE 17 7 0 03 Jan 2023
Physics-Informed Neural Networks for Prognostics and Health Management of Lithium-Ion Batteries Pengfei Wen Z. Ye Yong Li Shaowei Chen Pu Xie Shuai Zhao 14 35 0 02 Jan 2023
VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast and Accurate Prediction of Partial Differential Equations Bin Shan Ye Li Sheng-Jun Huang PINN 16 2 0 30 Nov 2022
A Dimension-Augmented Physics-Informed Neural Network (DaPINN) with High Level Accuracy and Efficiency Weilong Guan Kai-Ping Yang Yinsheng Chen Zhong Guan PINN AI4CE 6 12 0 19 Oct 2022
Failure-informed adaptive sampling for PINNs Zhiwei Gao Liang Yan Tao Zhou 16 76 0 01 Oct 2022
Stochastic Scaling in Loss Functions for Physics-Informed Neural Networks Ethan A Mills Alexey Pozdnyakov 11 0 0 07 Aug 2022
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks Shashank Subramanian Robert M. Kirby Michael W. Mahoney A. Gholami 14 25 0 08 Jul 2022
PhySRNet: Physics informed super-resolution network for application in computational solid mechanics Rajat Arora AI4CE 18 10 0 30 Jun 2022
Characterizing and Mitigating the Difficulty in Training Physics-informed Artificial Neural Networks under Pointwise Constraints S. Basir Inanc Senocak AI4CE 15 1 0 19 Jun 2022
Enhanced Physics-Informed Neural Networks with Augmented Lagrangian Relaxation Method (AL-PINNs) Hwijae Son S. Cho H. Hwang PINN 17 41 0 29 Apr 2022
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 98 272 0 20 Apr 2021
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 117 506 0 11 Mar 2020
Probabilistic Model-Agnostic Meta-Learning Chelsea Finn Kelvin Xu Sergey Levine BDL 165 666 0 07 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,659 0 09 Mar 2017