Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations

9 July 2024

Papers citing "Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations"

20 / 20 papers shown

Title
Verification and Validation for Trustworthy Scientific Machine Learning John D. Jakeman Lorena A. Barba J. Martins Thomas O'Leary-Roseberry AI4CE 76 0 0 21 Feb 2025
Can AI weather models predict out-of-distribution gray swan tropical cyclones? Y. Qiang Sun Pedram Hassanzadeh Mohsen Zand Ashesh Chattopadhyay Jonathan Weare D. Abbot 59 7 0 19 Oct 2024
Text2PDE: Latent Diffusion Models for Accessible Physics Simulation Anthony Zhou Zijie Li Michael Schneier John R Buchanan Jr Amir Barati Farimani AI4CE DiffM 99 6 0 02 Oct 2024
Discovery and inversion of the viscoelastic wave equation in inhomogeneous media Su Chen Yi Ding Hiroe Miyake Xiaojun Li 68 0 0 27 Sep 2024
PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers Phillip Lippe Bastiaan S. Veeling P. Perdikaris Richard Turner Johannes Brandstetter DiffM AI4CE 48 88 0 10 Aug 2023
E( $3$ ) Equivariant Graph Neural Networks for Particle-Based Fluid Mechanics Artur Toshev Gianluca Galletti Johannes Brandstetter Stefan Adami Nikolaus A. Adams 32 5 0 31 Mar 2023
Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils K. Shukla Vivek Oommen Ahmad Peyvan Michael Penwarden L. Bravo A. Ghoshal Robert M. Kirby George Karniadakis 52 20 0 02 Feb 2023
DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations) Matthieu Nastorg Marc Schoenauer Guillaume Charpiat T. Faney J. Gratien M. Bucci 54 2 0 21 Nov 2022
Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning J. Jeon Juhyeong Lee Ricardo Vinuesa S. J. Kim AI4CE 29 28 0 14 Jun 2022
Learning to Solve PDE-constrained Inverse Problems with Graph Networks Qingqing Zhao David B. Lindell Gordon Wetzstein AI4CE 58 40 0 01 Jun 2022
Simulating Liquids with Graph Networks Jonathan Klimesch Philipp Holl Nils Thuerey GNN AI4CE 57 8 0 14 Mar 2022
Multigrid-augmented deep learning preconditioners for the Helmholtz equation Yael Azulay Eran Treister AI4CE 53 30 0 14 Mar 2022
Machine Learning in the Search for New Fundamental Physics G. Karagiorgi Gregor Kasieczka S. Kravitz Benjamin Nachman David Shih AI4CE 49 113 0 07 Dec 2021
Physics-Informed Neural Operator for Learning Partial Differential Equations Zong-Yi Li Hongkai Zheng Nikola B. Kovachki David Jin Haoxuan Chen Burigede Liu Kamyar Azizzadenesheli Anima Anandkumar AI4CE 80 399 0 06 Nov 2021
Enhancing Computational Fluid Dynamics with Machine Learning Ricardo Vinuesa Steven L. Brunton AI4CE 143 363 0 05 Oct 2021
Improved architectures and training algorithms for deep operator networks Sizhuang He Hanwen Wang P. Perdikaris AI4CE 69 105 0 04 Oct 2021
Performance and accuracy assessments of an incompressible fluid solver coupled with a deep Convolutional Neural Network Ekhi Ajuria Illarramendi M. Bauerheim B. Cuenot 56 19 0 20 Sep 2021
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets Sizhuang He Hanwen Wang P. Perdikaris AI4CE 68 685 0 19 Mar 2021
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans M. Roberts D. Driggs Matthew Thorpe J. Gilbey Michael Yeung ... Kang Zhang S. Stranks James H. F. Rudd Evis Sala Carola-Bibiane Schönlieb OOD 38 768 0 14 Aug 2020
Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez Jonathan Godwin Tobias Pfaff Rex Ying J. Leskovec Peter W. Battaglia PINN AI4CE 101 1,065 0 21 Feb 2020