When and Why Adversarial Training Improves PINNs: A Neural Tangent Kernel Perspective

arXiv:2605.15959 · cs.LG, cs.AI · Submitted 2026-05-15 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-05-15

Updated: 2026-10-13

Terminology

• Adversarial Training — 3× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Generative Adversarial Networks (GANs) — 1× in this paper · explained in 3 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Physics-Informed Neural Networks (PINNs) — 1× in this paper · explained in 6 episodes

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks