PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks

1 February 2024

Papers citing "PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks"

21 / 21 papers shown

Title
Physics-informed Temporal Difference Metric Learning for Robot Motion Planning Ruiqi Ni Zherong Pan A. H. Qureshi SSL 29 0 0 09 May 2025
Mask-PINNs: Regulating Feature Distributions in Physics-Informed Neural Networks Feilong Jiang Xiaonan Hou Jianqiao Ye Min Xia OOD PINN 27 0 0 09 May 2025
Perception-Informed Neural Networks: Beyond Physics-Informed Neural Networks Mehran Mazandarani Marzieh Najariyan PINN AI4CE 28 0 0 02 May 2025
EquiNO: A Physics-Informed Neural Operator for Multiscale Simulations Hamidreza Eivazi Jendrik-Alexander Tröger Stefan H. A. Wittek Stefan Hartmann Andreas Rausch AI4CE 41 0 0 27 Mar 2025
Can Real-to-Sim Approaches Capture Dynamic Fabric Behavior for Robotic Fabric Manipulation? Yingdong Ru Lipeng Zhuang Zhuo He Florent P. Audonnet Gerardo Aragon-Caramasa AI4CE 51 0 0 20 Mar 2025
Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective Sifan Wang Ananyae Kumar Bhartari Bowen Li P. Perdikaris PINN 54 4 0 02 Feb 2025
About rectified sigmoid function for enhancing the accuracy of Physics-Informed Neural Networks V. A. Es'kin Alexey O. Malkhanov Mikhail E. Smorkalov MLT 41 0 0 31 Dec 2024
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases Madison Cooley Varun Shankar Robert M. Kirby Shandian Zhe 22 2 0 04 Oct 2024
HyResPINNs: Hybrid Residual Networks for Adaptive Neural and RBF Integration in Solving PDEs Madison Cooley Robert M. Kirby Shandian Zhe Varun Shankar PINN AI4CE 20 0 0 04 Oct 2024
Deep Learning Alternatives of the Kolmogorov Superposition Theorem Leonardo Ferreira Guilhoto P. Perdikaris 38 7 0 02 Oct 2024
KAN: Kolmogorov-Arnold Networks Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Soljacic Thomas Y. Hou Max Tegmark 72 460 0 30 Apr 2024
BiLO: Bilevel Local Operator Learning for PDE inverse problems Ray Zirui Zhang Xiaohui Xie John S. Lowengrub 63 1 0 27 Apr 2024
Learning in PINNs: Phase transition, total diffusion, and generalization Sokratis J. Anagnostopoulos Juan Diego Toscano Nikolaos Stergiopulos George Karniadakis 24 10 0 27 Mar 2024
Random Weight Factorization Improves the Training of Continuous Neural Representations Sifan Wang Hanwen Wang Jacob H. Seidman P. Perdikaris 21 9 0 03 Oct 2022
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 37 207 0 16 Jul 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 69 220 0 26 Apr 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sifan Wang Hanwen Wang P. Perdikaris 131 437 0 18 Dec 2020
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework O. Hennigh S. Narasimhan M. A. Nabian Akshay Subramaniam Kaustubh Tangsali M. Rietmann J. Ferrandis Wonmin Byeon Z. Fang S. Choudhry PINN AI4CE 91 125 0 14 Dec 2020
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 203 2,272 0 18 Oct 2020
Multi-scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains Ziqi Liu Wei Cai Zhi-Qin John Xu AI4CE 155 122 0 22 Jul 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 117 506 0 11 Mar 2020