The Julia Programming Language

Relax! Flux is the ML library that doesn't make you tensor

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equat…

Bayesian inference with probabilistic programming.

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Fast and simple fluid simulator in Julia

A reinforcement learning package for Julia

A Julia package for disciplined convex programming

An extensible framework for geospatial data science and geostatistical modeling fully written in Julia

Play atmospheric modelling like it's LEGO.

Probabilistic Programming with Gaussian processes in Julia

Julia for Machine Learning course at TU Berlin

Reservoir computing utilities for scientific machine learning (SciML)

Gaussian Process package based on data augmentation, sparsity and natural gradients

Fast inference for Gaussian processes in problems involving time. Partly built on results from https://proceedings.mlr.press/v161/tebbutt21a.html

NetCDF support for the julia programming language

Implements Optimization and approximate uncertainty quantification algorithms, Ensemble Kalman Inversion, and Ensemble Kalman Processes.

Stochastic Optimization, Learning, Uncertainty and Sampling

Automated Bayesian model discovery for time series data

Julia package for data manipulation and analysis

Code for paper https://arxiv.org/abs/2306.07961

Effortlessly uncover and label thematic insights in large document collections using the power of Large Language Models and Julia Language

A Julia package for operations research problems

A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.

Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data

Little pieces of code / Little pieces of...

Computation-Aware Kalman Filtering and RTS Smoothing

Vecchia approximations for Gaussian log-likelihoods

Bayesian inference on spatial and spatiotemporal data, faster than you can say "Cholesky!"