Dependency Packages
-
Flux.jl4466Relax! Flux is the ML library that doesn't make you tensor
-
Turing.jl2026Bayesian inference with probabilistic programming.
-
MLJ.jl1779A Julia machine learning framework
-
AlphaZero.jl1232A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.
-
NeuralPDE.jl966Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
-
NeuralNetDiffEq.jl966Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
-
TensorFlow.jl884A Julia wrapper for TensorFlow
-
DiffEqTutorials.jl713Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
-
FastAI.jl589Repository of best practices for deep learning in Julia, inspired by fastai
-
Transformers.jl521Julia Implementation of Transformer models
-
SpeedyWeather.jl425Play atmospheric modelling like it's LEGO.
-
DataDrivenDiffEq.jl405Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
-
Molly.jl389Molecular simulation in Julia
-
StatisticalRethinking.jl386Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.
-
GeometricFlux.jl348Geometric Deep Learning for Flux
-
Metalhead.jl328Computer vision models for Flux
-
MCMCChains.jl266Types and utility functions for summarizing Markov chain Monte Carlo simulations
-
NeuralOperators.jl262DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
-
AdvancedHMC.jl228Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
-
MLDatasets.jl227Utility package for accessing common Machine Learning datasets in Julia
-
GraphNeuralNetworks.jl218Graph Neural Networks in Julia
-
Stan.jl211Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.
-
CausalInference.jl189Causal inference, graphical models and structure learning in Julia
-
TopOpt.jl181A 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.
-
SeaPearl.jl168Julia hybrid constraint programming solver enhanced by a reinforcement learning driven search.
-
TuringModels.jl163Implementations of the models from the Statistical Rethinking book with Turing.jl
-
Omega.jl162Causal, Higher-Order, Probabilistic Programming
-
MLJBase.jl160Core functionality for the MLJ machine learning framework
-
DynamicPPL.jl157Implementation of domain-specific language (DSL) for dynamic probabilistic programming
-
RayTracer.jl150Differentiable RayTracing in Julia
-
InvertibleNetworks.jl149A Julia framework for invertible neural networks
-
MLJFlux.jl145Wrapping deep learning models from the package Flux.jl for use in the MLJ.jl toolbox
-
AugmentedGaussianProcesses.jl135Gaussian Process package based on data augmentation, sparsity and natural gradients
-
ConformalPrediction.jl135Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.
-
MPSKit.jl127A Julia package dedicated to simulating quantum many-body systems using Matrix Product States (MPS)
-
FluxArchitectures.jl123Complex neural network examples for Flux.jl
-
Kinetic.jl122Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.
-
DiffEqBayes.jl121Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
-
FluxTraining.jl119A flexible neural net training library inspired by fast.ai
-
CounterfactualExplanations.jl117A package for Counterfactual Explanations and Algorithmic Recourse in Julia.
Loading more...