Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil

Newt __ \/_ (' \`\ _\, \ \\/ /`\/\ \\ \ \\

JAX Models Table of Contents About The Project Getting Started Prerequisites Installation Usage Contributing License Contact About The Project The JAX

JAXGA - JAX Geometric Algebra GitHub | Docs JAXGA is a Geometric Algebra package on top of JAX. It can handle high dimensional algebras by storing onl

MUP for Haiku This is a (very preliminary) port of Yang and Hu et al.'s μP repo to Haiku and JAX. It's not feature complete, and I'm very open to sugg

This video in better quality. einops Flexible and powerful tensor operations for readable and reliable code. Supports numpy, pytorch, tensorflow, and

Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li

jax_dataclasses jax_dataclasses provides a wrapper around dataclasses.dataclass for use in JAX, which enables automatic support for: Pytree registrati

Factor graphs + nonlinear optimization in JAX

Map single-cell transcriptomes to copy number evolutionary trees. Check out the tutorial for more information. Installation $ pip install scatrex SCA

Treeo A small library for creating and manipulating custom JAX Pytree classes Light-weight: has no dependencies other than jax. Compatible: Treeo Tree

Treex A Pytree-based Module system for Deep Learning in JAX Intuitive: Modules are simple Python objects that respect Object-Oriented semantics and sh

Haiku: Sonnet for JAX Overview | Why Haiku? | Quickstart | Installation | Examples | User manual | Documentation | Citing Haiku What is Haiku? Haiku i

PIX PIX is an image processing library in JAX, for JAX. Overview JAX is a library resulting from the union of Autograd and XLA for high-performance ma

Extending JAX with custom C++ and CUDA code This repository is meant as a tutorial demonstrating the infrastructure required to provide custom ops in

A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:

Reinforcement learning library in JAX.

Optimal Model Design for Reinforcement Learning This repository contains JAX code for the paper Control-Oriented Model-Based Reinforcement Learning wi

Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries From the makers of spaCy, Prodigy and FastAPI Thinc is a

NeuralCompression is a Python repository dedicated to research of neural networks that compress data. The repository includes tools such as JAX-based entropy coders, image compression models, video c

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these enviro

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these enviro

FedJAX: Federated learning with JAX What is FedJAX? FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX. FedJAX priori

Flax: A neural network library and ecosystem for JAX designed for flexibility Overview | Quick install | What does Flax look like? | Documentation See

JAX: Autograd and XLA Quickstart | Transformations | Install guide | Neural net libraries | Change logs | Reference docs | Code search News: JAX tops

JAXopt Installation | Examples | References Hardware accelerated (GPU/TPU), batchable and differentiable optimizers in JAX. Installation JAXopt can be

Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural

Prompt Tuning This is the code to reproduce the experiments from the EMNLP 2021 paper "The Power of Scale for Parameter-Efficient Prompt Tuning" (Lest

Scenic Scenic is a codebase with a focus on research around attention-based models for computer vision. Scenic has been successfully used to develop c

Trax — Deep Learning with Clear Code and Speed Trax is an end-to-end library for deep learning that focuses on clear code and speed. It is actively us

tree-math: mathematical operations for JAX pytrees tree-math makes it easy to implement numerical algorithms that work on JAX pytrees, such as iterati

The purpose of this repo is to make it easy to get started with JAX. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I fou

Ivy is a templated deep learning framework which maximizes the portability of deep learning codebases. Ivy wraps the functional APIs of existing frameworks. Framework-agnostic functions, libraries an

Ivy vision focuses predominantly on 3D vision, with functions for camera geometry, image projections, co-ordinate frame transformations, forward warping, inverse warping, optical flow, depth triangul

KoCLIP This repository contains code for KoCLIP, a Korean port of OpenAI's CLIP. This project was conducted as part of Hugging Face's Flax/JAX communi

Use Jax functions in Pytorch with DLPack

MLP GPT - Jax (wip) A GPT, made only of MLPs, in Jax. The specific MLP to be used are gMLPs with the Spatial Gating Units. Working Pytorch implementat

Pretrained models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet.

Relaxed Machines Explorations in neuro-symbolic differentiable interpreters. Baby steps: inc_stop Libraries JAX Haiku Optax Resources Chapter 3 (∂4: A

RoBERTa base model for Marathi Language (मराठी भाषा) Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa wa

The Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more" Arxiv preprint Louay Hazami   ·   Rayhane Mama   ·   Ragavan Thurairatn

JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces JAXMAPP is a JAX-based library for multi-agent path planning (MAPP) in c

Diffrax Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. Diffrax is a JAX-based library providing numerical differe

Elegy Elegy is a framework-agnostic Trainer interface for the Jax ecosystem. Main Features Easy-to-use: Elegy provides a Keras-like high-level API tha

Python code for "Machine learning: a probabilistic perspective" (2nd edition)

Funsor Funsor is a tensor-like library for functions and distributions. See Functional tensors for probabilistic programming for a system description.

jax-variational-diffwave Jax/Flax implementation of Variational-DiffWave. (Zhifeng Kong et al., 2020, Diederik P. Kingma et al., 2021.) DiffWave with

Vision Transformers are Robust Learners This repository contains the code for the paper Vision Transformers are Robust Learners by Sayak Paul* and Pin

SOFIMA SOFIMA (Scalable Optical Flow-based Image Montaging and Alignment) is a tool for stitching, aligning and warping large 2d, 3d and 4d microscopy

Toy implementations of some popular ML optimizers using Python/JAX

Veros is the versatile ocean simulator -- it aims to be a powerful tool that makes high-performance ocean modeling approachable and fun. Because Veros

jaxdf - JAX-based Discretization Framework Overview | Example | Installation | Documentation ⚠️ This library is still in development. Breaking changes

The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv

PGMax implements general factor graphs for discrete probabilistic graphical models (PGMs), and hardware-accelerated differentiable loopy belief propagation (LBP) in JAX.

Infinitely Deep Bayesian Neural Networks with SDEs This library contains JAX and Pytorch implementations of neural ODEs and Bayesian layers for stocha

Maximum Likelihood Training of Score-Based Diffusion Models This repo contains the official implementation for the paper Maximum Likelihood Training o