Multi-language suite for high-performance solvers of differential equati...
Parallel Computing and Scientific Machine Learning (SciML): Methods and ...
An acausal modeling framework for automatically parallelized scientific ...
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differentia...
Tutorials for doing scientific machine learning (SciML) and high-perform...
PDEBench: An Extensive Benchmark for Scientific Machine Learning
High performance ordinary differential equation (ODE) and differential-a...
Solving differential equations in Python using DifferentialEquations.jl ...
Code accompanying my blog post: So, what is a physics-informed neural ne...
Chemical reaction network and systems biology interface for scientific m...
A component of the DiffEq ecosystem for enabling sensitivity analysis fo...
18.S096 - Applications of Scientific Machine Learning
The lightweight Base library for shared types and functionality for defi...
Scientific machine learning (SciML) benchmarks, AI for science, and (dif...
Linear operators for discretizations of differential equations and scien...