Fast uncertainty quantification for scientific machine learning (SciML) and differential equations

Fast uncertainty quantification for scientific machine learning (SciML) and differential equations

Building dynamical systems compositionally

Base functionality library for QuantumOptics.jl

Visualization for Flux.Chain neural networks

Multistart optimization methods in Julia.

Robot Motion Estimate: Tools, Variables, and Factors for SLAM in robotics; also see Caesar.jl.

An open source model predictive control package for Julia.

Rigorous function approximation using Taylor models in Julia

Fast and simple nonlinear solvers for the SciML common interface. Newton, Broyden, Bisection, Falsi, and more rootfinders on a standard interface.

A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

-

Darcy flow and reservoir simulator based on Jutul.jl

CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.

Model and solve optimal control problems in Julia

Atomic graph models for molecules and crystals in Julia

Conic Augmented Lagrangian Interior-Point SOlver

Choo-choo

Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions

Distributed Julia arrays using the MPI protocol

Import, process and interpret geophysical data sets to be used in numerical models.

High-level, high-performance, constraint-based reconstruction and analysis in Julia

Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.

Use Optim to train Flux models and visualize loss landscapes

A multi-dimensional, high performance deconvolution framework written in Julia Lang for CPUs and GPUs.

Julia wrapper for the performance monitoring and benchmarking suite LIKWID.

A Power Flow Solver for GPUs in Julia

A high functioning package detective.

Functions to compute omnidirectional landscape connectivity using circuit theory and the Omniscape algorithm.

Julia interface to Z3

Economic modeling in Julia

Plotting and interface tools for biology.

Distributed Data Parallel Training of Deep Neural Networks

Data-parallelism on CUDA using Transducers.jl and for loops (FLoops.jl)

A package with general tools for working with higher-dimensional tensor networks based on ITensor.

A static method overlay and optimization tool with configurable code generation and execution.

Julia interface to AMD/Radeon GPUs

Differentiable trajectory optimization in Julia.

Robust and optimal design and analysis of linear control systems

Segment-anything wrapped for Julia