flexible and efficient rolling window operations

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Blog posts on best practices for Julia development

The dispatch doctor prescribes type stability

An interface to various automatic differentiation backends in Julia.

A Julia package for simulation, inference and learning of Hidden Markov Models.

Boosts JupyterLab - proving tools to help you organise, explore and analyse your experimental data.

Benchmarks with back support

language level autograd compiler for Julia

A domain specific language (DSL) for probabilistic graphical models

Julia bindings for the Enzyme automatic differentiator

Julia implementation of computation-aware Gaussian Processes

A playbook for systematically maximizing the performance of deep learning models.

Package for different inducing points selection methods

A Julia RNG with stable streams

Time zone aware DateTimes, in UTC only

Aggregation of associative operators over rolling windows.

Julia installer and version multiplexer

A computational graph for time-series processing.

Preheat your MCMC

Add Conda dependencies to your Julia project

Python and Julia in harmony.

Provide all functions needed to work with augmented likelihoods (conditionally conjugate with Gaussians)

Simple & fast linear regression in Julia

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Interface for function inversion in Julia

Utilities for testing custom AD primitives.

Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX

Geographical plotting utilities for Makie.jl