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Solving parametric partial differential equations with deep rectified
  quadratic unit neural networks
v1v2 (latest)

Solving parametric partial differential equations with deep rectified quadratic unit neural networks

Journal of Scientific Computing (J. Sci. Comput.), 2022
14 March 2022
Zhen Lei
Lei Shi
Chenyu Zeng
ArXiv (abs)PDFHTML

Papers citing "Solving parametric partial differential equations with deep rectified quadratic unit neural networks"

5 / 5 papers shown
Operator Learning of Lipschitz Operators: An Information-Theoretic
  Perspective
Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective
Samuel Lanthaler
345
9
0
26 Jun 2024
An Efficient Deep Learning Approach for Approximating Parameter-to-Solution Maps of PDEs
An Efficient Deep Learning Approach for Approximating Parameter-to-Solution Maps of PDEs
Guanhang Lei
Zhen Lei
Lei Shi
Chenyu Zeng
176
0
0
10 Apr 2024
Learning smooth functions in high dimensions: from sparse polynomials to
  deep neural networks
Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks
Ben Adcock
Simone Brugiapaglia
N. Dexter
S. Moraga
217
8
0
04 Apr 2024
Operator Learning: Algorithms and Analysis
Operator Learning: Algorithms and Analysis
Nikola B. Kovachki
S. Lanthaler
Andrew M. Stuart
467
69
0
24 Feb 2024
CAS4DL: Christoffel Adaptive Sampling for function approximation via
  Deep Learning
CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep LearningSampling Theory, Signal Processing, and Data Analysis (TSPDA), 2022
Ben Adcock
Juan M. Cardenas
N. Dexter
200
13
0
25 Aug 2022
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