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Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure
Experimental results demonstrate that the proposed method improves the numerical accuracy of PINNs for partial differential equations.
Lyapunov-Stable Deep Equilibrium Models
Deep equilibrium (DEQ) models have emerged as a promising class of implicit layer models, which abandon traditional depth by solving for the fixed points of a single nonlinear layer.
Improving Neural ODEs via Knowledge Distillation
We propose a new training based on knowledge distillation to construct more powerful and robust Neural ODEs fitting image recognition tasks.
Towards Natural Robustness Against Adversarial Examples
Thus, Neural ODEs have natural robustness against adversarial examples.
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