Generate checklists and flow diagrams based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)

Accelerate your ML research using pre-built Deep Learning Models with Lux

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

Just the Comrade Models

Building and using pyramids for large raster data

Julia bindings for the Enzyme automatic differentiator

Preheat your MCMC

ClimaAtmos.jl is a library for building atmospheric circulation models that is designed from the outset to leverage data assimilation and machine learning tools. We welcome contributions!

Kite and tether models for the simulation of kite power systems

Clima's Land Model

Clima's Land Model

ClimaCoupler: bringing atmosphere, land, and ocean together

Basic functionality for EarthSciML system

Models of gas-phase atmospheric chemistry and related processes

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Data structures in Julia to enable power systems analysis. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

Implementation of domain-specific language (DSL) for dynamic probabilistic programming

🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs

A CPU- and GPU-friendly package for solving ordinary differential equations

Symbolic programming for the next generation of numerical software

Symbolic expressions, rewriting and simplification

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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 equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

Award winning software library for nonlinear dynamics and nonlinear timeseries analysis

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 and automated transformations of differential equations

Fundamentals of the control-toolbox ecosystem

Model and solve optimal control problems in Julia

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

Julia package to run Dynamic Power System simulations. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

High Level API Finite Element Methods based on ExtendableGrids and ExtendableFEMBase

A Julia package dedicated to simulating quantum many-body systems using Matrix Product States (MPS)

Gradient Ascent Pulse Engineering in Julia

Quantum dynamics simulation environment

Bayesian inference with probabilistic programming.

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

A Julia package for large-scale tensor computations, with a hint of category theory

Propagators for Quantum Dynamics and Optimal Control

Julia for optimization simulation and modeling of PowerSystems. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

Groebner bases in (almost) pure Julia