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GrADE: A graph based data-driven solver for time-dependent nonlinear
partial differential equations

GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations

24 August 2021

ArXiv (abs)PDF HTML Github

Papers citing "GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations"

6 / 6 papers shown

Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks

Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks

1.4K

20

0

29 Mar 2025

Deep Physics Corrector: A physics enhanced deep learning architecture
for solving stochastic differential equations

Deep Physics Corrector: A physics enhanced deep learning architecture for solving stochastic differential equationsJournal of Computational Physics (JCP), 2022

263

11

0

20 Sep 2022

Scalable algorithms for physics-informed neural and graph networks

Scalable algorithms for physics-informed neural and graph networksData-Centric Engineering (DE), 2022

George Karniadakis

391

56

0

16 May 2022

EINNs: Epidemiologically-informed Neural Networks

EINNs: Epidemiologically-informed Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2022

Alexander Rodríguez

Naren Ramakrishnan

395

48

0

21 Feb 2022

Gated Linear Model induced U-net for surrogate modeling and uncertainty
quantification

Gated Linear Model induced U-net for surrogate modeling and uncertainty quantification

Sai Krishna Mendu

218

2

0

08 Nov 2021

A deep learning based surrogate model for stochastic simulators

A deep learning based surrogate model for stochastic simulatorsProbabilistic Engineering Mechanics (PEM), 2021

308

21

0

24 Oct 2021

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