v1v2 (latest)

Learning continuous models for continuous physics

Communications Physics (Commun. Phys.), 2022

17 February 2022

Aditi S. Krishnapriyan

Papers citing "Learning continuous models for continuous physics"

24 / 24 papers shown

Title
Uncertainty-Aware Diagnostics for Physics-Informed Machine Learning Mara Daniels Liam Hodgkinson Michael W. Mahoney PINN AI4CE 231 0 0 30 Oct 2025
Interpretability and Generalization Bounds for Learning Spatial Physics Alejandro Francisco Queiruga Theo Gutman-Solo Shuai Jiang AI4CE 155 0 0 18 Jun 2025
Context parroting: A simple but tough-to-beat baseline for foundation models in scientific machine learning Yuanzhao Zhang William Gilpin AI4TS 171 1 0 16 May 2025
Neural equilibria for long-term prediction of nonlinear conservation laws Jose Antonio Lara Benitez Junyi Guo Kareem Hegazy Ivan Dokmanić Michael W. Mahoney Maarten V. de Hoop 198 4 0 12 Jan 2025
Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting Soon Hoe Lim Yijin Wang Annan Yu Emma Hart Michael W. Mahoney Xiaoye S. Li N. Benjamin Erichson AI4TS 403 7 0 04 Oct 2024
Zero-shot forecasting of chaotic systemsInternational Conference on Learning Representations (ICLR), 2024 Yuanzhao Zhang William Gilpin AI4TS 543 15 0 24 Sep 2024
Comparing and Contrasting Deep Learning Weather Prediction Backbones on Navier-Stokes and Atmospheric Dynamics Matthias Karlbauer Danielle C. Maddix Abdul Fatir Ansari Boran Han Gaurav Gupta Yuyang Wang Andrew Stuart Michael W. Mahoney AI4TS 266 4 0 19 Jul 2024
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning Wuyang Chen Jialin Song Pu Ren Shashank Subramanian Dmitriy Morozov Michael W. Mahoney AI4CE 368 20 0 24 Feb 2024
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modelingComputer Methods in Applied Mechanics and Engineering (CMAME), 2024 Nicholas Galioto Harsh Sharma Boris Kramer Alex Arkady Gorodetsky 273 1 0 23 Jan 2024
Reduced-order modeling for parameterized PDEs via implicit neural representations Tianshu Wen Kookjin Lee Youngsoo Choi AI4CE 190 8 0 28 Nov 2023
Stability-Informed Initialization of Neural Ordinary Differential EquationsInternational Conference on Machine Learning (ICML), 2023 Theodor Westny Arman Mohammadi Daniel Jung Erik Frisk 335 2 0 27 Nov 2023
OceanNet: A principled neural operator-based digital twin for regional oceansScientific Reports (Sci Rep), 2023 Ashesh Chattopadhyay Michael Gray Tianning Wu Anna B. Lowe Ruoying He AI4Cl 219 29 0 01 Oct 2023
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning Pu Ren N. Benjamin Erichson Shashank Subramanian Omer San Z. Lukić Michael W. Mahoney Michael W. Mahoney 220 22 0 24 Jun 2023
Towards Stability of Autoregressive Neural Operators Michael McCabe P. Harrington Shashank Subramanian Jed Brown AI4CE 361 33 0 18 Jun 2023
Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial informationComputers and Chemical Engineering (Comput. Chem. Eng.), 2023 S. Malani Tom S. Bertalan Tianqi Cui J. Avalos Michael Betenbaugh Ioannis G. Kevrekidis PINN AI4CE 143 5 0 27 Apr 2023
Learning Physical Models that Can Respect Conservation LawsInternational Conference on Machine Learning (ICML), 2023 Derek Hansen Danielle C. Maddix S. Alizadeh Gaurav Gupta Michael W. Mahoney AI4CE 326 61 0 21 Feb 2023
Continuous Spatiotemporal TransformersInternational Conference on Machine Learning (ICML), 2023 Antonio H. O. Fonseca E. Zappala J. O. Caro David van Dijk 160 10 0 31 Jan 2023
SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time Series Futoon M. Abushaqra Hao Xue Yongli Ren Flora D. Salim AI4TS 244 4 0 07 Dec 2022
Neural DAEs: Constrained neural networks Tue Boesen E. Haber Uri M. Ascher 314 3 0 25 Nov 2022
Learning differentiable solvers for systems with hard constraintsInternational Conference on Learning Representations (ICLR), 2022 Geoffrey Negiar Michael W. Mahoney Aditi S. Krishnapriyan 180 39 0 18 Jul 2022
Noisy Learning for Neural ODEs Acts as a Robustness Locus Widening Martin Gonzalez H. Hajri Loic Cantat Mihaly Petreczky 163 1 0 16 Jun 2022
On Numerical Integration in Neural Ordinary Differential EquationsInternational Conference on Machine Learning (ICML), 2022 Aiqing Zhu Pengzhan Jin Beibei Zhu Yifa Tang 197 30 0 15 Jun 2022
Characteristic Neural Ordinary Differential EquationsInternational Conference on Learning Representations (ICLR), 2021 Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 298 3 0 25 Nov 2021
Forecasting Sequential Data using Consistent Koopman AutoencodersInternational Conference on Machine Learning (ICML), 2020 Omri Azencot N. Benjamin Erichson Vanessa Lin Michael W. Mahoney AI4TS AI4CE 408 180 0 04 Mar 2020