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Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equat…
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…
Award winning software library for nonlinear dynamics and nonlinear timeseries analysis
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learni…
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
Modeling and simulation of multidomain engineering systems
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
Lattice reduction and other lattice tools in Julia
Helicopter Scientific Machine Learning (SciML) Challenge Problem
Implicit Runge-Kutta Gauss-Legendre 16th order (Julia)
A package to download free books from Springer using Julia
Official Implementation of "Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics" (ICML 2021)
Advanced Encryption Standard On-the-Fly mode in Julia