How Temporal Unrolling Supports Neural Physics Simulators

20 February 2024

Papers citing "How Temporal Unrolling Supports Neural Physics Simulators"

7 / 7 papers shown

Title
Eagle: Large-Scale Learning of Turbulent Fluid Dynamics with Mesh Transformers Steeven Janny Aurélien Béneteau Madiha Nadri Wolf Julie Digne Nicolas Thome Christian Wolf AI4CE 71 32 0 16 Feb 2023
Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts Rui Wang Yihe Dong Sercan Ö. Arik Rose Yu AI4TS 23 22 0 07 Oct 2022
A Fine-Grained Analysis on Distribution Shift Olivia Wiles Sven Gowal Florian Stimberg Sylvestre-Alvise Rebuffi Ira Ktena Krishnamurthy Dvijotham A. Cemgil OOD 215 196 0 21 Oct 2021
On the difficulty of learning chaotic dynamics with RNNs Jonas M. Mikhaeil Zahra Monfared Daniel Durstewitz 51 50 0 14 Oct 2021
A Perspective on Machine Learning Methods in Turbulence Modelling Andrea Beck Marius Kurz AI4CE 22 77 0 23 Oct 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 197 2,254 0 18 Oct 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 170 616 0 13 Mar 2020