ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1904.01514
  4. Cited By
Data driven approximation of parametrized PDEs by Reduced Basis and
  Neural Networks

Data driven approximation of parametrized PDEs by Reduced Basis and Neural Networks

2 April 2019
N. D. Santo
S. Deparis
Luca Pegolotti
ArXivPDFHTML

Papers citing "Data driven approximation of parametrized PDEs by Reduced Basis and Neural Networks"

13 / 13 papers shown
Title
Adaptive Multilevel Neural Networks for Parametric PDEs with Error
  Estimation
Adaptive Multilevel Neural Networks for Parametric PDEs with Error Estimation
Janina Enrica Schutte
Martin Eigel
AI4CE
27
2
0
19 Mar 2024
Addressing Discontinuous Root-Finding for Subsequent Differentiability
  in Machine Learning, Inverse Problems, and Control
Addressing Discontinuous Root-Finding for Subsequent Differentiability in Machine Learning, Inverse Problems, and Control
Dan Johnson
Ronald Fedkiw
AI4CE
21
2
0
21 Jun 2023
Neuro-symbolic partial differential equation solver
Neuro-symbolic partial differential equation solver
Pouria A. Mistani
Samira Pakravan
Rajesh Ilango
S. Choudhry
Frédéric Gibou
26
1
0
25 Oct 2022
JAX-DIPS: Neural bootstrapping of finite discretization methods and
  application to elliptic problems with discontinuities
JAX-DIPS: Neural bootstrapping of finite discretization methods and application to elliptic problems with discontinuities
Pouria A. Mistani
Samira Pakravan
Rajesh Ilango
Frédéric Gibou
16
8
0
25 Oct 2022
AI-enhanced iterative solvers for accelerating the solution of large
  scale parametrized systems
AI-enhanced iterative solvers for accelerating the solution of large scale parametrized systems
Stefanos Nikolopoulos
I. Kalogeris
V. Papadopoulos
G. Stavroulakis
16
11
0
06 Jul 2022
Learning To Estimate Regions Of Attraction Of Autonomous Dynamical
  Systems Using Physics-Informed Neural Networks
Learning To Estimate Regions Of Attraction Of Autonomous Dynamical Systems Using Physics-Informed Neural Networks
Cody Scharzenberger
Joe Hays
32
3
0
18 Nov 2021
Short-term traffic prediction using physics-aware neural networks
Short-term traffic prediction using physics-aware neural networks
M. Pereira
Annika Lang
Balázs Kulcsár
26
20
0
21 Sep 2021
Data-Driven Constitutive Relation Reveals Scaling Law for Hydrodynamic
  Transport Coefficients
Data-Driven Constitutive Relation Reveals Scaling Law for Hydrodynamic Transport Coefficients
Candi Zheng
Yang Wang
Shiying Chen
9
4
0
01 Aug 2021
Choose a Transformer: Fourier or Galerkin
Choose a Transformer: Fourier or Galerkin
Shuhao Cao
36
220
0
31 May 2021
Deep Neural Networks Are Effective At Learning High-Dimensional
  Hilbert-Valued Functions From Limited Data
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data
Ben Adcock
Simone Brugiapaglia
N. Dexter
S. Moraga
34
29
0
11 Dec 2020
Learning continuous-time PDEs from sparse data with graph neural
  networks
Learning continuous-time PDEs from sparse data with graph neural networks
V. Iakovlev
Markus Heinonen
Harri Lähdesmäki
AI4CE
16
68
0
16 Jun 2020
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs
Gitta Kutyniok
P. Petersen
Mones Raslan
R. Schneider
15
197
0
31 Mar 2019
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification
Yoon Kim
AILaw
VLM
255
13,364
0
25 Aug 2014
1