An Extensible Benchmark Suite for Learning to Simulate Physical Systems

An Extensible Benchmark Suite for Learning to Simulate Physical Systems

9 August 2021

Joan Bruna

Daniele Panozzo

Benjamin Peherstorfer

Papers citing "An Extensible Benchmark Suite for Learning to Simulate Physical Systems"

7 / 7 papers shown

Title
Learning to Predict Structural Vibrations J. V. Delden Julius Schultz Christopher Blech Sabine C. Langer Timo Luddecke AI4CE 26 1 0 09 Oct 2023
SimbaML: Connecting Mechanistic Models and Machine Learning with Augmented Data Maixmilian Kleissl Lukas Drews Benedict Heyder Julian Zabbarov Pascal Iversen Simon Witzke B. Renard Katharina Baum AI4CE 19 3 0 08 Apr 2023
AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions F. Bonnet Jocelyn Ahmed Mazari Paola Cinnella Patrick Gallinari AI4CE 25 54 0 15 Dec 2022
An extensible Benchmarking Graph-Mesh dataset for studying Steady-State Incompressible Navier-Stokes Equations F. Bonnet Jocelyn Ahmed Mazari T. Munzer P. Yser Patrick Gallinari AI4CE 51 10 0 29 Jun 2022
Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators Jonas Nicodemus Jonas Kneifl Jörg Fehr B. Unger PINN AI4CE 13 52 0 22 Sep 2021
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 143 219 0 29 Sep 2019
Reconstruction of Simulation-Based Physical Field by Reconstruction Neural Network Method Yu Li Hu Wang Kangjia Mo Tao Zeng 3DV AI4CE 22 7 0 19 Apr 2018