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. 2408.13101
  4. Cited By
Functional Tensor Decompositions for Physics-Informed Neural Networks

Functional Tensor Decompositions for Physics-Informed Neural Networks

23 August 2024
Sai Karthikeya Vemuri
Tim Buchner
Julia Niebling
Joachim Denzler
    PINN
ArXivPDFHTML

Papers citing "Functional Tensor Decompositions for Physics-Informed Neural Networks"

4 / 4 papers shown
Title
Respecting causality is all you need for training physics-informed
  neural networks
Respecting causality is all you need for training physics-informed neural networks
Sizhuang He
Shyam Sankaran
P. Perdikaris
PINN
CML
AI4CE
128
200
0
14 Mar 2022
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention
  Mechanism
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism
L. McClenny
U. Braga-Neto
PINN
68
452
0
07 Sep 2020
When and why PINNs fail to train: A neural tangent kernel perspective
When and why PINNs fail to train: A neural tangent kernel perspective
Sizhuang He
Xinling Yu
P. Perdikaris
109
896
0
28 Jul 2020
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
889
149,474
0
22 Dec 2014
1