A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

Surrogate modeling and optimization for scientific machine learning (SciML)

Computer vision models for Flux

XGBoost Julia Package

Automatic Differentiation Library for Computational and Mathematical Engineering

A Curious Cumulation of CUDA Cuisine

AMD GPU (ROCm) programming in Julia

Julia bindings to the FFTW library for fast Fourier transforms

Types and utility functions for summarizing Markov chain Monte Carlo simulations

DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia

:rocket: Julia package for orthogonal polynomial transforms :snowboarder:

Markov chain Monte Carlo (MCMC) for Bayesian analysis in julia

Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.

Utility package for accessing common Machine Learning datasets in Julia

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

Graph Neural Networks in Julia

Tidier data visualization in Julia, modeled after the ggplot2 R package.

Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.

Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains

Julia wrapper for the ArrayFire library

A Bayesian Analysis Toolkit in Julia

This library uses the LaTeX package pgfplots to produce plots.

A Julia package for fast discrete wavelet transforms and utilities

Tools for the exploration of chaos and nonlinear dynamics

Robust robotic localization and mapping, together with NavAbility(TM). Reach out to info@wherewhen.ai for help.

A package for binary and continuous, single and multi-material, truss and continuum, 2D and 3D topology optimization on unstructured meshes using automatic differentiation in Julia.

Kernel density estimators for Julia

Boosted trees in Julia

Fast, general-purpose interactive applications for complex systems

Julia hybrid constraint programming solver enhanced by a reinforcement learning driven search.

Implementations of the models from the Statistical Rethinking book with Turing.jl

Causal, Higher-Order, Probabilistic Programming

Geophysical fluid dynamics pseudospectral solvers with Julia and FourierFlows.jl.

Differentiable RayTracing in Julia

A Julia framework for invertible neural networks

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Algorithms for quantifying associations, independence testing and causal inference from data.

A Julia package for strided array views and efficient manipulations thereof

Algorithms for quantifying associations, independence testing and causal inference from data.

Wrapping deep learning models from the package Flux.jl for use in the MLJ.jl toolbox