Deflation-PINNs: Learning Multiple Solutions for PDEs and Landau-de Gennes
math.NA, cs.LG, cs.NA
Submitted: 2026-03-30
Updated: 2026-08-28
Code: https://github.com/SeanDisaro/DeflationPINNs
Terminology
Sources
- Operator Learning at Machine Precision
- The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems
- Variational Physics-Informed Neural Networks For Solving Partial Differential Equations
- Error estimates for DeepOnets: A deep learning framework in infinite dimensions
- Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations
- Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations
- Neural Network-Based Tensor Model for Nematic Liquid Crystals with Accurate Microscopic Information
- Inferring turbulent velocity and temperature fields and their statistics from Lagrangian velocity measurements using physics-informed Kolmogorov-Arnold Networks
- An Expert's Guide to Training Physics-informed Neural Networks
- Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble
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