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JAX - A curated list of resources https://github.com/google/jax

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[ Daily / Weekly / Overview ]

Apr 29 - May 05, 2024

Libraries / New Libraries

• EasyDeL - EasyDeL 🔮 is an OpenSource Library to make your training faster and more Optimized With cool Options for training and serving (Llama, MPT, Mixtral, Falcon, etc) in JAX

• dynamiqs - High-performance and differentiable simulations of quantum systems with JAX.

Apr 01 - Apr 07, 2024

Libraries

• Levanter - Legible, Scalable, Reproducible Foundation Models with Named Tensors and JAX.

• EasyLM - LLMs made easy: Pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.

Community / NumPyro

• JaxLLM (Unofficial) Discord

Dec 25 - Dec 31, 2023

Libraries / New Libraries

• XLB - A Differentiable Massively Parallel Lattice Boltzmann Library in Python for Physics-Based Machine Learning.

Papers / NumPyro

• XLB: A Differentiable Massively Parallel Lattice Boltzmann Library in Python. Mohammadmehdi Ataei, Hesam Salehipour. arXiv 2023. - White paper describing the XLB library: benchmarks, validations, and more details about the library.

Dec 18 - Dec 24, 2023

Libraries / New Libraries

• Spyx - Spiking Neural Networks in JAX for machine learning on neuromorphic hardware.

Oct 23 - Oct 29, 2023

Libraries / New Libraries

• JAX Toolbox - Nightly CI and optimized examples for JAX on NVIDIA GPUs using libraries such as T5x, Paxml, and Transformer Engine.

• Pgx - Vectorized board game environments for RL with an AlphaZero example.

Tutorials and Blog Posts / NumPyro

• Learn JAX: From Linear Regression to Neural Networks by Rito Ghosh - A gentle introduction to JAX and using it to implement Linear and Logistic Regression, and Neural Network models and using them to solve real world problems.

Sep 25 - Oct 01, 2023

Libraries

• BlackJAX - Library of samplers for JAX.

Sep 18 - Sep 24, 2023

Libraries / New Libraries

• QDax - Quality Diversity optimization in Jax.

Sep 11 - Sep 17, 2023

Libraries / New Libraries

• MaxText - A simple, performant and scalable Jax LLM written in pure Python/Jax and targeting Google Cloud TPUs.

• Pax - A Jax-based machine learning framework for training large scale models.

• Praxis - The layer library for Pax with a goal to be usable by other JAX-based ML projects.

• purejaxrl - Vectorisable, end-to-end RL algorithms in JAX.

• Lorax - Automatically apply LoRA to JAX models (Flax, Haiku, etc.)

• SCICO - Scientific computational imaging in JAX.

• BrainPy - Brain Dynamics Programming in Python.

• OTT-JAX - Optimal transport tools in JAX.

Tutorials and Blog Posts / NumPyro

• Achieving 4000x Speedups with PureJaxRL - A blog post on how JAX can massively speedup RL training through vectorisation.

Mar 20 - Mar 26, 2023

Libraries / New Libraries

• Kernex - Differentiable stencil decorators in JAX.

Mar 06 - Mar 12, 2023

Libraries / New Libraries

• safejax - Serialize JAX, Flax, Haiku, or Objax model params with 🤗safetensors.

Jan 23 - Jan 29, 2023

Libraries / New Libraries

• jax-tqdm - Add a tqdm progress bar to JAX scans and loops.

Jan 09 - Jan 15, 2023

Models and Projects / Flax

• GNNs for Solving Combinatorial Optimization Problems (⭐38) - A JAX + Flax implementation of Combinatorial Optimization with Physics-Inspired Graph Neural Networks.

Jan 02 - Jan 08, 2023

Libraries / New Libraries

• SPU - A domain-specific compiler and runtime suite to run JAX code with MPC(Secure Multi-Party Computation).

Dec 26 - Jan 01, 2022

Libraries

• Fortuna - AWS library for Uncertainty Quantification in Deep Learning.

Nov 14 - Nov 20, 2022

Libraries / New Libraries

• econpizza - Solve macroeconomic models with hetereogeneous agents using JAX.

Oct 17 - Oct 23, 2022

Models and Projects / NumPyro

• lqg (⭐23) - Official implementation of Bayesian inverse optimal control for linear-quadratic Gaussian problems from the paper Putting perception into action with inverse optimal control for continuous psychophysics

Sep 05 - Sep 11, 2022

Libraries / New Libraries

• JAXFit - Accelerated curve fitting library for nonlinear least-squares problems (see arXiv paper).

Aug 29 - Sep 04, 2022

Libraries / New Libraries

• GPJax - Gaussian processes in JAX.

• Jumanji - A Suite of Industry-Driven Hardware-Accelerated RL Environments written in JAX.

• Eqxvision - Equinox version of Torchvision.

Models and Projects / Flax

• Sharpened Cosine Similarity in JAX by Raphael Pisoni - A JAX/Flax implementation of the Sharpened Cosine Similarity layer.

Tutorials and Blog Posts / NumPyro

• Writing a Training Loop in JAX + FLAX by Saurav Maheshkar and Soumik Rakshit - A tutorial on writing a simple end-to-end training and evaluation pipeline in JAX, Flax and Optax.

• Implementing NeRF in JAX by Soumik Rakshit and Saurav Maheshkar - A tutorial on 3D volumetric rendering of scenes represented by Neural Radiance Fields in JAX.

• Deep Learning tutorials with JAX+Flax by Phillip Lippe - A series of notebooks explaining various deep learning concepts, from basics (e.g. intro to JAX/Flax, activiation functions) to recent advances (e.g., Vision Transformers, SimCLR), with translations to PyTorch.

Aug 22 - Aug 28, 2022

Books / NumPyro

• Jax in Action - A hands-on guide to using JAX for deep learning and other mathematically-intensive applications.

Aug 08 - Aug 14, 2022

Libraries / New Libraries

• jwave - A library for differentiable acoustic simulations

Jun 27 - Jul 03, 2022

Libraries / New Libraries

• Mctx - Monte Carlo tree search algorithms in native JAX.

• KFAC-JAX - Second Order Optimization with Approximate Curvature for NNs.

• TF2JAX - Convert functions/graphs to JAX functions.

Jun 20 - Jun 26, 2022

Libraries / New Libraries

• gymnax - Reinforcement Learning Environments with the well-known gym API.

Mar 14 - Mar 20, 2022

Libraries / New Libraries

• Einshape - DSL-based reshaping library for JAX and other frameworks.

• ALX - Open-source library for distributed matrix factorization using Alternating Least Squares, more info in ALX: Large Scale Matrix Factorization on TPUs.

• Diffrax - Numerical differential equation solvers in JAX.

• tinygp - The tiniest of Gaussian process libraries in JAX.

Models and Projects / JAX

• Symbolic Functionals - Demonstration from Evolving symbolic density functionals.

• TriMap - Official JAX implementation of TriMap: Large-scale Dimensionality Reduction Using Triplets.

Models and Projects / Flax

• mip-NeRF - Official implementation of Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields.

• RegNeRF - Official implementation of RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputs.

• ARDM (⭐33k) - Official implementation of Autoregressive Diffusion Models.

• D3PM (⭐33k) - Official implementation of Structured Denoising Diffusion Models in Discrete State-Spaces.

• Gumbel-max Causal Mechanisms (⭐33k) - Code for Learning Generalized Gumbel-max Causal Mechanisms, with extra code in GuyLor/gumbel_max_causal_gadgets_part2 (⭐2).

• Latent Programmer (⭐33k) - Code for the ICML 2021 paper Latent Programmer: Discrete Latent Codes for Program Synthesis.

• SNeRG (⭐33k) - Official implementation of Baking Neural Radiance Fields for Real-Time View Synthesis.

• Spin-weighted Spherical CNNs (⭐33k) - Adaptation of Spin-Weighted Spherical CNNs.

• VDVAE (⭐33k) - Adaptation of Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images, original code at openai/vdvae (⭐427).

• MUSIQ (⭐33k) - Checkpoints and model inference code for the ICCV 2021 paper MUSIQ: Multi-scale Image Quality Transformer

• AQuaDem (⭐33k) - Official implementation of Continuous Control with Action Quantization from Demonstrations.

• Combiner (⭐33k) - Official implementation of Combiner: Full Attention Transformer with Sparse Computation Cost.

• Dreamfields (⭐33k) - Official implementation of the ICLR 2022 paper Progressive Distillation for Fast Sampling of Diffusion Models.

• GIFT (⭐33k) - Official implementation of Gradual Domain Adaptation in the Wild:When Intermediate Distributions are Absent.

• Light Field Neural Rendering (⭐33k) - Official implementation of Light Field Neural Rendering.

Feb 28 - Mar 06, 2022

Libraries / New Libraries

• Neural Network Libraries
  • FedJAX - Federated learning in JAX, built on Optax and Haiku.
  • Equivariant MLP - Construct equivariant neural network layers.
  • jax-resnet - Implementations and checkpoints for ResNet variants in Flax.
  • Parallax - Immutable Torch Modules for JAX.

Feb 21 - Feb 27, 2022

Libraries / New Libraries

• evosax - JAX-Based Evolution Strategies

• SymJAX - Symbolic CPU/GPU/TPU programming.

• mcx - Express & compile probabilistic programs for performant inference.

Feb 14 - Feb 20, 2022

Libraries / New Libraries

• EvoJAX - Hardware-Accelerated Neuroevolution

Feb 07 - Feb 13, 2022

Libraries / New Libraries

• PGMax - A framework for building discrete Probabilistic Graphical Models (PGM's) and running inference inference on them via JAX.

Tutorials and Blog Posts / NumPyro

• Get started with JAX by Aleksa Gordić (⭐559) - A series of notebooks and videos going from zero JAX knowledge to building neural networks in Haiku.

Jan 24 - Jan 30, 2022

Libraries / New Libraries

• tree-math - Convert functions that operate on arrays into functions that operate on PyTrees.

• jax-models - Implementations of research papers originally without code or code written with frameworks other than JAX.

Jan 03 - Jan 09, 2022

Tutorials and Blog Posts / NumPyro

• Introduction to JAX by Kevin Murphy - Colab that introduces various aspects of the language and applies them to simple ML problems.

Dec 27 - Jan 02, 2021

Models and Projects / Haiku

• Two Player Auction Learning (⭐0) - JAX implementation of the paper Auction learning as a two-player game.

Nov 08 - Nov 14, 2021

Libraries / New Libraries

• JaxDF - Framework for differentiable simulators with arbitrary discretizations.

Sep 06 - Sep 12, 2021

Libraries / New Libraries

• bayex - Bayesian Optimization powered by JAX.

Aug 09 - Aug 15, 2021

Libraries

• Neural Network Libraries
  • Flax - Centered on flexibility and clarity.
  • Haiku - Focused on simplicity, created by the authors of Sonnet at DeepMind.
  • Objax - Has an object oriented design similar to PyTorch.
  • Elegy - A High Level API for Deep Learning in JAX. Supports Flax, Haiku, and Optax.
  • Trax - "Batteries included" deep learning library focused on providing solutions for common workloads.
  • Jraph - Lightweight graph neural network library.
  • Neural Tangents - High-level API for specifying neural networks of both finite and infinite width.
  • HuggingFace - Ecosystem of pretrained Transformers for a wide range of natural language tasks (Flax).
  • Equinox - Callable PyTrees and filtered JIT/grad transformations => neural networks in JAX.
  • Scenic - A Jax Library for Computer Vision Research and Beyond.

Jul 26 - Aug 01, 2021

Models and Projects / JAX

• Amortized Bayesian Optimization - Code related to Amortized Bayesian Optimization over Discrete Spaces.

• Accurate Quantized Training - Tools and libraries for running and analyzing neural network quantization experiments in JAX and Flax.

• BNN-HMC - Implementation for the paper What Are Bayesian Neural Network Posteriors Really Like?.

• JAX-DFT - One-dimensional density functional theory (DFT) in JAX, with implementation of Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics.

• Robust Loss - Reference code for the paper A General and Adaptive Robust Loss Function.

Models and Projects / Flax

• Performer - Flax implementation of the Performer (linear transformer via FAVOR+) architecture.

• JaxNeRF - Implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis with multi-device GPU/TPU support.

• Big Transfer (BiT) - Implementation of Big Transfer (BiT): General Visual Representation Learning.

• JAX RL - Implementations of reinforcement learning algorithms.

• gMLP - Implementation of Pay Attention to MLPs.

• MLP Mixer - Minimal implementation of MLP-Mixer: An all-MLP Architecture for Vision.

• Distributed Shampoo - Implementation of Second Order Optimization Made Practical.

• NesT - Official implementation of Aggregating Nested Transformers.

• XMC-GAN - Official implementation of Cross-Modal Contrastive Learning for Text-to-Image Generation.

• FNet - Official implementation of FNet: Mixing Tokens with Fourier Transforms.

• GFSA - Official implementation of Learning Graph Structure With A Finite-State Automaton Layer.

• IPA-GNN - Official implementation of Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks.

• Flax Models (⭐33k) - Collection of models and methods implemented in Flax.

• Protein LM (⭐33k) - Implements BERT and autoregressive models for proteins, as described in Biological Structure and Function Emerge from Scaling Unsupervised Learning to 250 Million Protein Sequences and ProGen: Language Modeling for Protein Generation.

• Slot Attention (⭐33k) - Reference implementation for Differentiable Patch Selection for Image Recognition.

• Vision Transformer (⭐9.3k) - Official implementation of An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

• FID computation (⭐21) - Port of mseitzer/pytorch-fid (⭐3.1k) to Flax.

Models and Projects / Haiku

• AlphaFold (⭐12k) - Implementation of the inference pipeline of AlphaFold v2.0, presented in Highly accurate protein structure prediction with AlphaFold.

• Adversarial Robustness (⭐13k) - Reference code for Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples and Fixing Data Augmentation to Improve Adversarial Robustness.

• Bootstrap Your Own Latent (⭐13k) - Implementation for the paper Bootstrap your own latent: A new approach to self-supervised Learning.

• Gated Linear Networks (⭐13k) - GLNs are a family of backpropagation-free neural networks.

• Glassy Dynamics (⭐13k) - Open source implementation of the paper Unveiling the predictive power of static structure in glassy systems.

• MMV (⭐13k) - Code for the models in Self-Supervised MultiModal Versatile Networks.

• Normalizer-Free Networks (⭐13k) - Official Haiku implementation of NFNets.

• NuX (⭐82) - Normalizing flows with JAX.

• OGB-LSC (⭐13k) - This repository contains DeepMind's entry to the PCQM4M-LSC (quantum chemistry) and MAG240M-LSC (academic graph) tracks of the OGB Large-Scale Challenge (OGB-LSC).

• Persistent Evolution Strategies (⭐33k) - Code used for the paper Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies.

• WikiGraphs (⭐13k) - Baseline code to reproduce results in WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Datase.

Models and Projects / Trax

• Reformer (⭐8k) - Implementation of the Reformer (efficient transformer) architecture.

Videos / NumPyro

• JAX, Flax & Transformers 🤗 (⭐125k) - 3 days of talks around JAX / Flax, Transformers, large-scale language modeling and other great topics.

Jul 19 - Jul 25, 2021

Libraries / New Libraries

• JAXopt - Hardware accelerated (GPU/TPU), batchable and differentiable optimizers in JAX.

• PIX - PIX is an image processing library in JAX, for JAX.

Jul 12 - Jul 18, 2021

Libraries

• NetKet - Machine Learning toolbox for Quantum Physics.

Jun 07 - Jun 13, 2021

Libraries / New Libraries

• flaxmodels - Pretrained models for Jax/Flax.

• CR.Sparse - XLA accelerated algorithms for sparse representations and compressive sensing.

• exojax - Automatic differentiable spectrum modeling of exoplanets/brown dwarfs compatible to JAX.

Tutorials and Blog Posts / NumPyro

• Writing an MCMC sampler in JAX by Jeremie Coullon - Tutorial on the different ways to write an MCMC sampler in JAX along with speed benchmarks.

• How to add a progress bar to JAX scans and loops by Jeremie Coullon - Tutorial on how to add a progress bar to compiled loops in JAX using the host_callback module.

May 31 - Jun 06, 2021

Libraries / New Libraries

• jaxlie - Lie theory library for rigid body transformations and optimization.

• BRAX - Differentiable physics engine to simulate environments along with learning algorithms to train agents for these environments.

May 24 - May 30, 2021

Libraries / New Libraries

• delta PV - A photovoltaic simulator with automatic differentation.

May 17 - May 23, 2021

Libraries

• Coax - Turn RL papers into code, the easy way.

Apr 26 - May 02, 2021

Libraries

• Distrax - Reimplementation of TensorFlow Probability, containing probability distributions and bijectors.

• cvxpylayers - Construct differentiable convex optimization layers.

• TensorLy - Tensor learning made simple.

Mar 15 - Mar 21, 2021

Libraries / New Libraries

• Optimal Transport Tools - Toolbox that bundles utilities to solve optimal transport problems.

Mar 01 - Mar 07, 2021

Libraries

• RLax - Library for implementing reinforcement learning agents.

Libraries / New Libraries

• FlaxVision - Flax version of TorchVision.

• Oryx - Probabilistic programming language based on program transformations.

Videos / NumPyro

• Solving y=mx+b with Jax on a TPU Pod slice - Mat Kelcey - A four part YouTube tutorial series with Colab notebooks that starts with Jax fundamentals and moves up to training with a data parallel approach on a v3-32 TPU Pod slice.

Tutorials and Blog Posts / NumPyro

• Deterministic ADVI in JAX by Martin Ingram - Walk through of implementing automatic differentiation variational inference (ADVI) easily and cleanly with JAX.

• Evolved channel selection by Mat Kelcey - Trains a classification model robust to different combinations of input channels at different resolutions, then uses a genetic algorithm to decide the best combination for a particular loss.

Feb 22 - Feb 28, 2021

Libraries / New Libraries

• imax - Image augmentations and transformations.

Feb 08 - Feb 14, 2021

Tutorials and Blog Posts / NumPyro

• Exploring hyperparameter meta-loss landscapes with JAX by Luke Metz - Demonstrates how to use JAX to perform inner-loss optimization with SGD and Momentum, outer-loss optimization with gradients, and outer-loss optimization using evolutionary strategies.

Feb 01 - Feb 07, 2021

Tutorials and Blog Posts / NumPyro

• Out of distribution (OOD) detection by Mat Kelcey - Implements different methods for OOD detection.

• Extending JAX with custom C++ and CUDA code by Dan Foreman-Mackey (⭐353) - Tutorial demonstrating the infrastructure required to provide custom ops in JAX.

• Evolving Neural Networks in JAX by Robert Tjarko Lange - Explores how JAX can power the next generation of scalable neuroevolution algorithms.

Jan 25 - Jan 31, 2021

Libraries

• NumPyro - Probabilistic programming based on the Pyro library.

• Chex - Utilities to write and test reliable JAX code.

• Optax - Gradient processing and optimization library.

• JAX, M.D. - Accelerated, differential molecular dynamics.

Libraries / New Libraries

• jax-unirep - Library implementing the UniRep model for protein machine learning applications.

• jax-cosmo - Differentiable cosmology library.

Videos / NumPyro

• Introduction to JAX - Simple neural network from scratch in JAX.

Papers / NumPyro

• Compiling machine learning programs via high-level tracing. Roy Frostig, Matthew James Johnson, Chris Leary. MLSys 2018. - White paper describing an early version of JAX, detailing how computation is traced and compiled.

Tutorials and Blog Posts / NumPyro

• Plugging Into JAX by Nick Doiron - Compares Flax, Haiku, and Objax on the Kaggle flower classification challenge.

Jan 18 - Jan 24, 2021

Models and Projects / JAX

• Fourier Feature Networks - Official implementation of Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains.

Videos / NumPyro

• NeurIPS 2020: JAX Ecosystem Meetup - JAX, its use at DeepMind, and discussion between engineers, scientists, and JAX core team.

• JAX: Accelerated Machine Learning Research | SciPy 2020 | VanderPlas - JAX's core design, how it's powering new research, and how you can start using it.

• Bayesian Programming with JAX + NumPyro — Andy Kitchen - Introduction to Bayesian modelling using NumPyro.

• JAX on Cloud TPUs | NeurIPS 2020 | Skye Wanderman-Milne and James Bradbury - Presentation of TPU host access with demo.

• Deep Implicit Layers - Neural ODEs, Deep Equilibirum Models, and Beyond | NeurIPS 2020 - Tutorial created by Zico Kolter, David Duvenaud, and Matt Johnson with Colab notebooks avaliable in Deep Implicit Layers.

Papers / NumPyro

• JAX, M.D.: A Framework for Differentiable Physics. Samuel S. Schoenholz, Ekin D. Cubuk. NeurIPS 2020. - Introduces JAX, M.D., a differentiable physics library which includes simulation environments, interaction potentials, neural networks, and more.

• Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization. Pranav Subramani, Nicholas Vadivelu, Gautam Kamath. arXiv 2020. - Uses JAX's JIT and VMAP to achieve faster differentially private than existing libraries.

Tutorials and Blog Posts / NumPyro

• Using JAX to accelerate our research by David Budden and Matteo Hessel - Describes the state of JAX and the JAX ecosystem at DeepMind.

• Getting started with JAX (MLPs, CNNs & RNNs) by Robert Lange - Neural network building blocks from scratch with the basic JAX operators.

• Tutorial: image classification with JAX and Flax Linen by 8bitmp3 (⭐22) - Learn how to create a simple convolutional network with the Linen API by Flax and train it to recognize handwritten digits.

• Meta-Learning in 50 Lines of JAX by Eric Jang - Introduction to both JAX and Meta-Learning.

• Normalizing Flows in 100 Lines of JAX by Eric Jang - Concise implementation of RealNVP.

• Differentiable Path Tracing on the GPU/TPU by Eric Jang - Tutorial on implementing path tracing.

• Ensemble networks by Mat Kelcey - Ensemble nets are a method of representing an ensemble of models as one single logical model.

• Understanding Autodiff with JAX by Srihari Radhakrishna - Understand how autodiff works using JAX.

• From PyTorch to JAX: towards neural net frameworks that purify stateful code by Sabrina J. Mielke - Showcases how to go from a PyTorch-like style of coding to a more Functional-style of coding.

Jan 04 - Jan 10, 2021

Libraries / New Libraries

• mpi4jax - Combine MPI operations with your Jax code on CPUs and GPUs.

Jan 04 - Jan 10, 2021

Libraries / New Libraries

• jax-flows - Normalizing flows in JAX.

• sklearn-jax-kernels - scikit-learn kernel matrices using JAX.

• efax - Exponential Families in JAX.

Models and Projects / JAX

• kalman-jax - Approximate inference for Markov (i.e., temporal) Gaussian processes using iterated Kalman filtering and smoothing.

• jaxns - Nested sampling in JAX.

Dec 28 - Jan 03, 2020

Videos / NumPyro

• JAX: Accelerated machine-learning research via composable function transformations in Python | NeurIPS 2019 | Skye Wanderman-Milne - JAX intro presentation in Program Transformations for Machine Learning workshop.

Dec 21 - Dec 27, 2020

Community / NumPyro

• JAX GitHub Discussions (⭐28k)

• Reddit