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. 2302.01810
  4. Cited By
PINN Training using Biobjective Optimization: The Trade-off between Data
  Loss and Residual Loss

PINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss

3 February 2023
Fabian Heldmann
Sarah Treibert
Matthias Ehrhardt
K. Klamroth
ArXivPDFHTML

Papers citing "PINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss"

3 / 3 papers shown
Title
PINNverse: Accurate parameter estimation in differential equations from noisy data with constrained physics-informed neural networks
PINNverse: Accurate parameter estimation in differential equations from noisy data with constrained physics-informed neural networks
Marius Almanstötter
Roman Vetter
Dagmar Iber
PINN
29
1
0
07 Apr 2025
Meta-learning PINN loss functions
Meta-learning PINN loss functions
Apostolos F. Psaros
Kenji Kawaguchi
George Karniadakis
PINN
35
96
0
12 Jul 2021
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and
  Inverse PDE Problems with Noisy Data
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
Liu Yang
Xuhui Meng
George Karniadakis
PINN
170
756
0
13 Mar 2020
1