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2402.00972
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Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-based Reinforcement Learning
1 February 2024
Jan-Philipp von Bassewitz
Sebastian Kaltenbach
Petros Koumoutsakos
AI4CE
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Papers citing
"Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-based Reinforcement Learning"
31 / 31 papers shown
Reinforcement Learning Closures for Underresolved Partial Differential Equations using Synthetic Data
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Petr Karnakov
Francis J. Alexander
Petros Koumoutsakos
AI4CE
398
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0
16 May 2025
Optimal Lattice Boltzmann Closures through Multi-Agent Reinforcement Learning
Paul Fischer
Sebastian Kaltenbach
Sergey Litvinov
Sauro Succi
Petros Koumoutsakos
AI4CE
257
2
0
19 Apr 2025
PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers
Neural Information Processing Systems (NeurIPS), 2023
Phillip Lippe
Bastiaan S. Veeling
P. Perdikaris
Richard Turner
Johannes Brandstetter
DiffM
AI4CE
575
179
0
10 Aug 2023
Towards Multi-spatiotemporal-scale Generalized PDE Modeling
Jayesh K. Gupta
Johannes Brandstetter
AI4CE
416
202
0
30 Sep 2022
Clifford Neural Layers for PDE Modeling
International Conference on Learning Representations (ICLR), 2022
Johannes Brandstetter
Rianne van den Berg
Max Welling
Jayesh K. Gupta
AI4CE
403
117
0
08 Sep 2022
Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems
Computational Mechanics (Comput. Mech.), 2022
Sebastian Kaltenbach
P. Perdikaris
P. Koutsourelakis
378
37
0
06 Sep 2022
Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning
Conference on Robot Learning (CoRL), 2022
Homer Walke
Jonathan Yang
Albert Yu
Aviral Kumar
Jedrzej Orbik
Avi Singh
Sergey Levine
OffRL
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336
39
0
11 Jul 2022
NOMAD: Nonlinear Manifold Decoders for Operator Learning
Neural Information Processing Systems (NeurIPS), 2022
Jacob H. Seidman
Georgios Kissas
P. Perdikaris
George J. Pappas
AI4CE
399
102
0
07 Jun 2022
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem
Neural Information Processing Systems (NeurIPS), 2022
Muning Wen
J. Kuba
Runji Lin
Weinan Zhang
Ying Wen
Jun Wang
Yaodong Yang
452
305
0
30 May 2022
Jump-Start Reinforcement Learning
International Conference on Machine Learning (ICML), 2022
Ikechukwu Uchendu
Ted Xiao
Yao Lu
Banghua Zhu
Mengyuan Yan
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Chuyuan Fu
Cong Ma
Jiantao Jiao
Sergey Levine
Karol Hausman
OffRL
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445
157
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05 Apr 2022
Respecting causality is all you need for training physics-informed neural networks
Sizhuang He
Shyam Sankaran
P. Perdikaris
PINN
CML
AI4CE
533
243
0
14 Mar 2022
Reward-Respecting Subtasks for Model-Based Reinforcement Learning
Artificial Intelligence (AIJ), 2022
R. Sutton
Marlos C. Machado
G. Z. Holland
David Szepesvari Finbarr Timbers
Finbarr Timbers
B. Tanner
Adam White
401
29
0
07 Feb 2022
Learning Cooperative Multi-Agent Policies with Partial Reward Decoupling
IEEE Robotics and Automation Letters (RA-L), 2021
B. Freed
Aditya Kapoor
Ian Abraham
J. Schneider
Howie Choset
206
8
0
23 Dec 2021
Tianshou: a Highly Modularized Deep Reinforcement Learning Library
Journal of machine learning research (JMLR), 2021
Jiayi Weng
Huayu Chen
Dong Yan
Kaichao You
Alexis Duburcq
Minghao Zhang
Yi Su
Hang Su
Jun Zhu
NoLa
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467
253
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29 Jul 2021
Scientific multi-agent reinforcement learning for wall-models of turbulent flows
Nature Communications (Nat Commun), 2021
H. J. Bae
Petros Koumoutsakos
AI4CE
308
172
0
21 Jun 2021
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
Science Advances (Sci Adv), 2021
Sizhuang He
Hanwen Wang
P. Perdikaris
AI4CE
599
1,022
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19 Mar 2021
Physics-aware, probabilistic model order reduction with guaranteed stability
International Conference on Learning Representations (ICLR), 2021
Sebastian Kaltenbach
P. Koutsourelakis
DiffM
AI4CE
342
16
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14 Jan 2021
Inductive Biases for Deep Learning of Higher-Level Cognition
Proceedings of the Royal Society A (Proc. R. Soc. A), 2020
Anirudh Goyal
Yoshua Bengio
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626
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30 Nov 2020
Fourier Neural Operator for Parametric Partial Differential Equations
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Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
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Emmanuel de Bézenac
Ibrahim Ayed
Nicolas Thome
Patrick Gallinari
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531
165
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09 Oct 2020
Lagrangian Neural Networks
International Conference on Learning Representations (ICLR), 2020
M. Cranmer
S. Greydanus
Stephan Hoyer
Peter W. Battaglia
D. Spergel
S. Ho
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672
558
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10 Mar 2020
Incorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systems
Journal of Computational Physics (JCP), 2019
Sebastian Kaltenbach
P. Koutsourelakis
AI4CE
573
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30 Dec 2019
PixelRL: Fully Convolutional Network with Reinforcement Learning for Image Processing
IEEE transactions on multimedia (IEEE TMM), 2019
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Naoto Inoue
T. Yamasaki
262
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16 Dec 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Nature Machine Intelligence (NMI), 2019
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Hamiltonian Neural Networks
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Misko Dzamba
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PINN
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