Dependency Packages
-
Flux.jl4122Relax! Flux is the ML library that doesn't make you tensor
-
DifferentialEquations.jl2503Multi-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.
-
Turing.jl1807Bayesian inference with probabilistic programming.
-
Knet.jl1403Koç University deep learning framework.
-
ModelingToolkit.jl1212An 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
-
AlphaZero.jl1131A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.
-
CUDA.jl974CUDA programming in Julia.
-
DSGE.jl798Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)
-
Oceananigans.jl781🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs
-
DiffEqFlux.jl771Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
-
NeuralPDE.jl755Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
-
NeuralNetDiffEq.jl755Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
-
DiffEqTutorials.jl694Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
-
FastAI.jl557Repository of best practices for deep learning in Julia, inspired by fastai
-
QuantumOptics.jl459Library for the numerical simulation of closed as well as open quantum systems.
-
Transformers.jl420Julia Implementation of Transformer models
-
WaterLily.jl405Fast and simple fluid simulator in Julia
-
DataDrivenDiffEq.jl372Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
-
TensorOperations.jl351Julia package for tensor contractions and related operations
-
DiffEqBiological.jl342Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software
-
Catalyst.jl342Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software
-
GeometricFlux.jl330Geometric Deep Learning for Flux
-
Modia.jl298Modeling and simulation of multidomain engineering systems
-
Metalhead.jl297Computer vision models for Flux
-
Molly.jl281Molecular simulation in Julia
-
XGBoost.jl262XGBoost Julia Package
-
SpeedyWeather.jl256The little sister of a big weather forecast model
-
DiffEqSensitivity.jl248A 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.
-
SciMLSensitivity.jl248A 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.
-
ParallelStencil.jl238Package for writing high-level code for parallel high-performance stencil computations that can be deployed on both GPUs and CPUs
-
StochasticDiffEq.jl200Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
-
BAT.jl164A Bayesian Analysis Toolkit in Julia
-
Coluna.jl161Branch-and-Price-and-Cut in Julia
-
FourierFlows.jl161Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains
-
Omega.jl155Causal, Higher-Order, Probabilistic Programming
-
GraphNeuralNetworks.jl153Graph Neural Networks in Julia
-
TuringModels.jl153Implementations of the models from the Statistical Rethinking book with Turing.jl
-
NeuralOperators.jl151DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
-
EvoTrees.jl143Boosted trees in Julia
-
OMEinsum.jl143One More Einsum for Julia! With runtime order-specification and high-level adjoints for AD
Loading more...