Physics-Informed-Neural-Networks-for-Quantum-Dynamics

A library for scientific machine learning and physics-informed learning

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

Brian is a free, open source simulator for spiking neural networks.

Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)

Code accompanying my blog post: So, what is a physics-informed neural network?

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

? Numerically solving and backpropagating through the wave equation

Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.