Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equat…

Julia kernel for Jupyter

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning a…

Compile your Julia Package

⚡ Single-pass algorithms for statistics

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

Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization

Julia code for the book Reinforcement Learning An Introduction

Symbolic parser for Julia language term rewriting using REDUCE algebra

An expression-level debugger for Julia with a provocative command-line (REPL) user interface

Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning

Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)

GraphQL for Julia

Charlotte's Web Scale

A Julia project demonstrating the fast f-k migration algorithm.

Charlotte's Web Scale