Learning continuous models for continuous physics

17 February 2022

Aditi S. Krishnapriyan

Papers citing "Learning continuous models for continuous physics"

22 / 22 papers shown

Title
Context parroting: A simple but tough-to-beat baseline for foundation models in scientific machine learning Yuanzhao Zhang William Gilpin AI4TS 17 0 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 38 0 0 12 Jan 2025
Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting S. H. Lim Yijin Wang Annan Yu Emma Hart Michael W. Mahoney Xiaoye S. Li N. Benjamin Erichson AI4TS 47 1 0 04 Oct 2024
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 37 4 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 56 1 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 52 12 0 24 Feb 2024
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling Nicholas Galioto Harsh Sharma Boris Kramer Alex Arkady Gorodetsky 44 0 0 23 Jan 2024
Reduced-order modeling for parameterized PDEs via implicit neural representations Tianshu Wen Kookjin Lee Youngsoo Choi AI4CE 50 5 0 28 Nov 2023
Stability-Informed Initialization of Neural Ordinary Differential Equations Theodor Westny Arman Mohammadi Daniel Jung Erik Frisk 28 0 0 27 Nov 2023
OceanNet: A principled neural operator-based digital twin for regional oceans A. Chattopadhyay Michael Gray Tianning Wu Anna B. Lowe Ruoying He AI4Cl 27 13 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 44 13 0 24 Jun 2023
Towards Stability of Autoregressive Neural Operators Michael McCabe P. Harrington Shashank Subramanian Jed Brown AI4CE 44 17 0 18 Jun 2023
Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information S. Malani Tom S. Bertalan Tianqi Cui J. Avalos Michael Betenbaugh Ioannis G. Kevrekidis PINN AI4CE 37 4 0 27 Apr 2023
Learning Physical Models that Can Respect Conservation Laws Derek Hansen Danielle C. Maddix S. Alizadeh Gaurav Gupta Michael W. Mahoney AI4CE 42 42 0 21 Feb 2023
Continuous Spatiotemporal Transformers Antonio H. O. Fonseca E. Zappala J. O. Caro David van Dijk 26 7 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 26 2 0 07 Dec 2022
Neural DAEs: Constrained neural networks Tue Boesen E. Haber Uri M. Ascher 39 3 0 25 Nov 2022
Learning differentiable solvers for systems with hard constraints Geoffrey Negiar Michael W. Mahoney Aditi S. Krishnapriyan 31 28 0 18 Jul 2022
Noisy Learning for Neural ODEs Acts as a Robustness Locus Widening Martin Gonzalez H. Hajri Loic Cantat Mihaly Petreczky 34 1 0 16 Jun 2022
On Numerical Integration in Neural Ordinary Differential Equations Aiqing Zhu Pengzhan Jin Beibei Zhu Yifa Tang 26 26 0 15 Jun 2022
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 29 3 0 25 Nov 2021
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 152 220 0 29 Sep 2019