Machine Learning for Partial Differential Equations

30 March 2023

Steven L. Brunton

Papers citing "Machine Learning for Partial Differential Equations"

23 / 23 papers shown

Title
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
Data-driven identification of latent port-Hamiltonian systems J. Rettberg Jonas Kneifl Julius Herb Patrick Buchfink Jörg Fehr B. Haasdonk PINN 16 2 0 15 Aug 2024
Reducing Spatial Discretization Error on Coarse CFD Simulations Using an OpenFOAM-Embedded Deep Learning Framework Jesus Gonzalez-Sieiro David Pardo Vincenzo Nava V. M. Calo Markus Towara AI4CE 17 1 0 13 May 2024
Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks R. Mattey Susanta Ghosh AI4CE 33 1 0 09 May 2024
BiLO: Bilevel Local Operator Learning for PDE inverse problems Ray Zirui Zhang Xiaohui Xie John S. Lowengrub 63 1 0 27 Apr 2024
Nonlinear model reduction for operator learning Hamidreza Eivazi Stefan H. A. Wittek Andreas Rausch 19 3 0 27 Mar 2024
JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework Artur P. Toshev Harish D. Ramachandran Jonas A. Erbesdobler Gianluca Galletti Johannes Brandstetter Nikolaus A. Adams 44 7 0 07 Mar 2024
Operator Learning: Algorithms and Analysis Nikola B. Kovachki S. Lanthaler Andrew M. Stuart 36 22 0 24 Feb 2024
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics Artur P. Toshev Jonas A. Erbesdobler Nikolaus A. Adams Johannes Brandstetter AI4CE 38 4 0 09 Feb 2024
Speeding up and reducing memory usage for scientific machine learning via mixed precision Joel Hayford Jacob Goldman-Wetzler Eric Wang Lu Lu 36 3 0 30 Jan 2024
Weak-Form Latent Space Dynamics Identification April Tran Xiaolong He Daniel Messenger Youngsoo Choi David M. Bortz 29 7 0 20 Nov 2023
PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers Phillip Lippe Bastiaan S. Veeling P. Perdikaris Richard E. Turner Johannes Brandstetter DiffM AI4CE 28 76 0 10 Aug 2023
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions Ben Adcock Juan M. Cardenas N. Dexter 16 6 0 01 Jun 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 11 10 0 27 Apr 2023
A Novel Sparse Regularizer Hovig Bayandorian 20 0 0 18 Jan 2023
Clifford Neural Layers for PDE Modeling Johannes Brandstetter Rianne van den Berg Max Welling Jayesh K. Gupta AI4CE 60 79 0 08 Sep 2022
Enhancing Computational Fluid Dynamics with Machine Learning Ricardo Vinuesa Steven L. Brunton AI4CE 98 351 0 05 Oct 2021
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 2,254 0 18 Oct 2020
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs P. D. Haan Maurice Weiler Taco S. Cohen Max Welling 89 127 0 11 Mar 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 121 419 0 10 Mar 2020
Data-Driven Discovery of Coarse-Grained Equations Joseph Bakarji D. Tartakovsky 16 32 0 30 Jan 2020
Learning Symbolic Physics with Graph Networks M. Cranmer Rui Xu Peter W. Battaglia S. Ho PINN AI4CE 177 83 0 12 Sep 2019
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics C. Wehmeyer Frank Noé AI4CE BDL 109 355 0 30 Oct 2017