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Physics-Informed Neural Network Super Resolution for Advection-Diffusion
  Models

Physics-Informed Neural Network Super Resolution for Advection-Diffusion Models

4 November 2020
Chulin Wang
E. Bentivegna
Wang Zhou
L. Klein
Bruce Elmegreen
    DiffM
ArXivPDFHTML

Papers citing "Physics-Informed Neural Network Super Resolution for Advection-Diffusion Models"

11 / 11 papers shown
Title
Representing Flow Fields with Divergence-Free Kernels for Reconstruction
Representing Flow Fields with Divergence-Free Kernels for Reconstruction
Xingyu Ni
Jingrui Xing
Xingqiao Li
Bin Wang
Baoquan Chen
AI4CE
38
0
0
02 Apr 2025
How to Re-enable PDE Loss for Physical Systems Modeling Under Partial
  Observation
How to Re-enable PDE Loss for Physical Systems Modeling Under Partial Observation
Haodong Feng
Yue Wang
Dixia Fan
AI4CE
75
0
0
12 Dec 2024
Filtered Partial Differential Equations: a robust surrogate constraint
  in physics-informed deep learning framework
Filtered Partial Differential Equations: a robust surrogate constraint in physics-informed deep learning framework
Dashan Zhang
Yuntian Chen
Shiyi Chen
AI4CE
32
2
0
07 Nov 2023
An Operator Learning Framework for Spatiotemporal Super-resolution of
  Scientific Simulations
An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations
Valentin Duruisseaux
Amit Chakraborty
AI4CE
16
1
0
04 Nov 2023
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning
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
36
13
0
24 Jun 2023
Physics-Informed Computer Vision: A Review and Perspectives
Physics-Informed Computer Vision: A Review and Perspectives
C. Banerjee
Kien Nguyen
Clinton Fookes
G. Karniadakis
PINN
AI4CE
34
28
0
29 May 2023
Tools for Extracting Spatio-Temporal Patterns in Meteorological Image
  Sequences: From Feature Engineering to Attention-Based Neural Networks
Tools for Extracting Spatio-Temporal Patterns in Meteorological Image Sequences: From Feature Engineering to Attention-Based Neural Networks
A. S. Bansal
Yoonjin Lee
Kyle Hilburn
I. Ebert‐Uphoff
AI4TS
31
2
0
22 Oct 2022
Rotationally Equivariant Super-Resolution of Velocity Fields in
  Two-Dimensional Fluids Using Convolutional Neural Networks
Rotationally Equivariant Super-Resolution of Velocity Fields in Two-Dimensional Fluids Using Convolutional Neural Networks
Y. Yasuda
R. Onishi
17
5
0
22 Feb 2022
Adversarial sampling of unknown and high-dimensional conditional
  distributions
Adversarial sampling of unknown and high-dimensional conditional distributions
M. Hassanaly
Andrew Glaws
Karen Stengel
Ryan N. King
GAN
19
21
0
08 Nov 2021
The Old and the New: Can Physics-Informed Deep-Learning Replace
  Traditional Linear Solvers?
The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?
Stefano Markidis
PINN
36
182
0
12 Mar 2021
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time
  Super-Resolution Framework
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework
C. Jiang
S. Esmaeilzadeh
Kamyar Azizzadenesheli
K. Kashinath
Mustafa A. Mustafa
H. Tchelepi
P. Marcus
P. Prabhat
Anima Anandkumar
AI4CE
187
141
0
01 May 2020
1