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Finite Volume Neural Network: Modeling Subsurface Contaminant Transport

Finite Volume Neural Network: Modeling Subsurface Contaminant Transport

13 April 2021
T. Praditia
Matthias Karlbauer
S. Otte
S. Oladyshkin
Martin Volker Butz
Wolfgang Nowak
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Finite Volume Neural Network: Modeling Subsurface Contaminant Transport"

14 / 14 papers shown
A nudge to the truth: atom conservation as a hard constraint in models
  of atmospheric composition using an uncertainty-weighted correction
A nudge to the truth: atom conservation as a hard constraint in models of atmospheric composition using an uncertainty-weighted correction
Patrick Obin Sturm
Sam J. Silva
234
0
0
28 Aug 2024
Inferring Underwater Topography with FINN
Inferring Underwater Topography with FINN
Coşku Can Horuz
Matthias Karlbauer
T. Praditia
S. Oladyshkin
Wolfgang Nowak
Sebastian Otte
AI4CE
234
0
0
20 Aug 2024
Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations
Automatic Differentiation is Essential in Training Neural Networks for Solving Differential EquationsJournal of Scientific Computing (J. Sci. Comput.), 2024
Chuqi Chen
Yahong Yang
Yang Xiang
Wenrui Hao
354
17
0
23 May 2024
GrINd: Grid Interpolation Network for Scattered Observations
GrINd: Grid Interpolation Network for Scattered Observations
Andrzej Dulny
Paul Heinisch
Andreas Hotho
Anna Krause
306
1
0
28 Mar 2024
TaylorPDENet: Learning PDEs from non-grid Data
TaylorPDENet: Learning PDEs from non-grid Data
Paul Heinisch
Andrzej Dulny
Anna Krause
Andreas Hotho
OODDiffMAI4CE
175
0
0
26 Jun 2023
DynaBench: A benchmark dataset for learning dynamical systems from
  low-resolution data
DynaBench: A benchmark dataset for learning dynamical systems from low-resolution data
Andrzej Dulny
Andreas Hotho
Anna Krause
AI4CE
360
8
0
09 Jun 2023
On the Relationships between Graph Neural Networks for the Simulation of
  Physical Systems and Classical Numerical Methods
On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods
Artur Toshev
Ludger Paehler
A. Panizza
Nikolaus A. Adams
AI4CEPINN
330
5
0
31 Mar 2023
Efficient hybrid modeling and sorption model discovery for non-linear
  advection-diffusion-sorption systems: A systematic scientific machine
  learning approach
Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approachChemical Engineering and Science (CES), 2023
Vinícius V. Santana
É. Costa
C. Rebello
A. M. Ribeiro
Chris Rackauckas
Idelfonso B. R. Nogueira
254
19
0
22 Mar 2023
Towards Multi-spatiotemporal-scale Generalized PDE Modeling
Towards Multi-spatiotemporal-scale Generalized PDE Modeling
Jayesh K. Gupta
Johannes Brandstetter
AI4CE
415
202
0
30 Sep 2022
Clifford Neural Layers for PDE Modeling
Clifford Neural Layers for PDE ModelingInternational Conference on Learning Representations (ICLR), 2022
Johannes Brandstetter
Rianne van den Berg
Max Welling
Jayesh K. Gupta
AI4CE
403
117
0
08 Sep 2022
Composing Partial Differential Equations with Physics-Aware Neural
  Networks
Composing Partial Differential Equations with Physics-Aware Neural Networks
Matthias Karlbauer
T. Praditia
S. Otte
S. Oladyshkin
Wolfgang Nowak
Martin Volker Butz
AI4CE
312
29
0
23 Nov 2021
NeuralPDE: Modelling Dynamical Systems from Data
NeuralPDE: Modelling Dynamical Systems from DataDeutsche Jahrestagung für Künstliche Intelligenz (KI), 2021
Andrzej Dulny
Andreas Hotho
Anna Krause
AI4CE
206
15
0
15 Nov 2021
Finite volume method network for acceleration of unsteady computational
  fluid dynamics: non-reacting and reacting flows
Finite volume method network for acceleration of unsteady computational fluid dynamics: non-reacting and reacting flowsInternational Journal of Energy Research (IJER), 2021
J. Jeon
Juhyeong Lee
S. J. Kim
313
41
0
07 May 2021
Deep Learning of Subsurface Flow via Theory-guided Neural Network
Deep Learning of Subsurface Flow via Theory-guided Neural NetworkJournal of Hydrology (J. Hydrol.), 2019
Nanzhe Wang
Dongxiao Zhang
Haibin Chang
Heng Li
AI4CE
443
288
0
24 Oct 2019
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