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. 2301.04887
  4. Cited By
Learning Partial Differential Equations by Spectral Approximates of
  General Sobolev Spaces

Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces

12 January 2023
Juan Esteban Suarez Cardona
Phil-Alexander Hofmann
Michael Hecht
ArXivPDFHTML

Papers citing "Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces"

3 / 3 papers shown
Title
Ensuring Topological Data-Structure Preservation under Autoencoder
  Compression due to Latent Space Regularization in Gauss--Legendre nodes
Ensuring Topological Data-Structure Preservation under Autoencoder Compression due to Latent Space Regularization in Gauss--Legendre nodes
Chethan Krishnamurthy Ramanaik
Juan Esteban Suarez Cardona
Anna Willmann
Pia Hanfeld
Nico Hoffmann
Michael Hecht
14
1
0
15 Sep 2023
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain
  Decomposition
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition
E. Kharazmi
Zhongqiang Zhang
George Karniadakis
128
508
0
11 Mar 2020
Linear Convergence of Gradient and Proximal-Gradient Methods Under the
  Polyak-Łojasiewicz Condition
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition
Hamed Karimi
J. Nutini
Mark W. Schmidt
139
1,201
0
16 Aug 2016
1