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abstractgps.jl

Abstract types and methods for Gaussian Processes.

ad-kernels

Code for the paper "Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields"

adventofcode

http://adventofcode.com/

blackjax

BlackJAX is a sampling library designed for ease of use, speed and modularity.

blog

chainrules.jl

forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs

chainrulescore.jl

It is like recipes but for AD! (Full functionality is in ChainRules.jl but this a light weight dependency just to define sensitivities for your functions in your packages)

chainrulesdeclarationhelpers.jl

Helpers for declaring ChainRules

deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

deepqlearning

small experiments with agents learning atari games, implemented in jax/numpy

dex-lang

Research language for array processing in the Haskell/ML family

dftfunctionals.jl

Interface and Julia implementation of exchange-correlation functionals

dftk.jl

Density-functional toolkit

differentiabledftk

Automatic differentiation for density functional theory in Julia.

diffopt.jl

Differentiating convex optimization program w.r.t. program parameters

diffractor.jl

Next-generation AD

distances.jl

A Julia package for evaluating distances (metrics) between vectors.

elegy

A High Level API for Deep Learning in JAX

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fastai

The fast.ai deep learning library, lessons, and tutorials

fax

forwarddiff.jl

Forward Mode Automatic Differentiation for Julia

galacticoptim.jl

Local, global, and beyond optimization for scientific machine learning (SciML)

gpytorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

graphs.jl

An optimized graphs package for the Julia programming language

instant-ngp

Instant neural graphics primitives: lightning fast NeRF and more

jax

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

jax-md

Differentiable, Hardware Accelerated, Molecular Dynamics

kmnist

Repository for Kuzushiji-MNIST, Kuzushiji-49, and Kuzushiji-Kanji

maml-jax

Implementation of Model-Agnostic Meta-Learning (MAML) in Jax