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Neural Conservation Laws: A Divergence-Free Perspective

Neural Conservation Laws: A Divergence-Free Perspective

4 October 2022
Jack Richter-Powell
Y. Lipman
Ricky T. Q. Chen
ArXivPDFHTML

Papers citing "Neural Conservation Laws: A Divergence-Free Perspective"

13 / 13 papers shown
Title
Learning and Transferring Physical Models through Derivatives
Learning and Transferring Physical Models through Derivatives
Alessandro Trenta
Andrea Cossu
Davide Bacciu
AI4CE
26
0
0
02 May 2025
Unsupervised Representation Learning from Sparse Transformation Analysis
Unsupervised Representation Learning from Sparse Transformation Analysis
Yue Song
Thomas Anderson Keller
Yisong Yue
Pietro Perona
Max Welling
DRL
14
0
0
07 Oct 2024
Transport-Embedded Neural Architecture: Redefining the Landscape of
  physics aware neural models in fluid mechanics
Transport-Embedded Neural Architecture: Redefining the Landscape of physics aware neural models in fluid mechanics
Amirmahdi Jafari
11
0
0
05 Oct 2024
Differentiable programming across the PDE and Machine Learning barrier
Differentiable programming across the PDE and Machine Learning barrier
N. Bouziani
David A. Ham
Ado Farsi
PINN
AI4CE
14
1
0
09 Sep 2024
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for
  Machine Learning and Process-based Hydrology
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology
Qingsong Xu
Yilei Shi
Jonathan Bamber
Ye Tuo
Ralf Ludwig
Xiao Xiang Zhu
AI4CE
10
9
0
08 Oct 2023
Learning Latent Dynamics via Invariant Decomposition and
  (Spatio-)Temporal Transformers
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers
Kai Lagemann
C. Lagemann
Swarnava Mukherjee
16
2
0
21 Jun 2023
Fast Dynamic 1D Simulation of Divertor Plasmas with Neural PDE
  Surrogates
Fast Dynamic 1D Simulation of Divertor Plasmas with Neural PDE Surrogates
Y. Poels
G. Derks
E. Westerhof
Koen Minartz
Sven Wiesen
Vlado Menkovski
3DGS
AI4CE
6
15
0
30 May 2023
Invariant preservation in machine learned PDE solvers via error
  correction
Invariant preservation in machine learned PDE solvers via error correction
N. McGreivy
Ammar Hakim
AI4CE
PINN
13
8
0
28 Mar 2023
Exact conservation laws for neural network integrators of dynamical
  systems
Exact conservation laws for neural network integrators of dynamical systems
E. Müller
PINN
29
12
0
23 Sep 2022
Generative Modeling with Optimal Transport Maps
Generative Modeling with Optimal Transport Maps
Litu Rout
Alexander Korotin
Evgeny Burnaev
OT
DiffM
114
65
0
06 Oct 2021
Convex Potential Flows: Universal Probability Distributions with Optimal
  Transport and Convex Optimization
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang
Ricky T. Q. Chen
Christos Tsirigotis
Aaron Courville
OT
101
95
0
10 Dec 2020
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
228
3,202
0
24 Nov 2016
Input Convex Neural Networks
Input Convex Neural Networks
Brandon Amos
Lei Xu
J. Zico Kolter
163
596
0
22 Sep 2016
1