physics-informed-ml
Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularization
Learning function operators with neural networks.
Physics-based machine learning with dynamic Boltzmann distributions
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
