Training + Physics Informed

14.0

Package a Python library for discrete weak formulation of PDEs into a user-friendly API. This enables researchers to define custom discrete neural network representations for scientific computing.

emergingimplementation gap

trainingtoolphysics-informedoptimization

Signals (2)

arXiv1d ago

Python library supporting Discrete Variational Formulations and training solutions with Collocation-based Robust Variational Physics Informed Neural Networks (DVF-CRVPINN)

arXiv1d ago

Training + Physics Informed

Signals (2)

Python library supporting Discrete Variational Formulations and training solutions with Collocation-based Robust Variational Physics Informed Neural Networks (DVF-CRVPINN)

Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks

Training + Physics Informed

Signals (2)

Python library supporting Discrete Variational Formulations and training solutions with Collocation-based Robust Variational Physics Informed Neural Networks (DVF-CRVPINN)

Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks