Reverse Dependencies of jax

The following projects have a declared dependency on jax:

• absl-extra — A wrapper to run and monitor absl app.
• accurating — AccuRating is a library for accurate player ranking based on match results.
• acqdp — Alibaba Cloud Quantum Development Platform
• adam-core — Core libraries for the ADAM platform
• adam-robotics — Automatic Differentiation for rigid-body-dynamics AlgorithMs
• adastra — Astra - Pytorch
• advanced-global-optimizers — A package that integrates many advanced global optimizers
• aex — Sampling with Blackjax on Aesara
• agent-torch — large population models
• agjax — A jax wrapper for autograd-differentiable functions.
• ai2-tango — A library for choreographing your machine learning research.
• aironsuit — A model wrapper for automatic model design and visualization purposes.
• ajents — RL agents in JAX
• alpa — Alpa automatically parallelizes large tensor computation graphs and runs them on a distributed cluster.
• alphafold — An implementation of the inference pipeline of AlphaFold v2.0.This is a completely new model that was entered as AlphaFold2 in CASP14 and published in Nature.
• alphafold-colabfold — An implementation of the inference pipeline of AlphaFold v2.3.1. This is a completely new model that was entered as AlphaFold2 in CASP14 and published in Nature. This package contains patches for colabfold.
• alphafold-kagglefold — An implementation of the inference pipeline of AlphaFold v2.0.This is a completely new model that was entered as AlphaFold2 in CASP14 and published in Nature. This package contains patches for kagglefold
• alquitable — Keras-core based tools to enhance Alquimodelia
• anabel — An end to end differentiable finite element framework.
• anacal — no summary
• ananke-causal — Ananke, named for the Greek primordial goddess of necessity and causality, is a python package for causal inference using the language of graphical models.
• angmom-suite — A package for working with phenomenological spin and angular momentum operators
• annax — Fast and memory-efficient approximate nearest neighbor search with JAX
• anon — Research workspace.
• anyboxes — Lightweight package for managing bounding boxes that works seamlessly with most computing frameworks.
• apax — Atomistic Learned Potential Package in JAX
• appletree — A high-Performance Program simuLatEs and fiTs REsponse of xEnon.
• aqsc — Constructs QS stellarator equilibrium to all orders.
• aqtp — Accurate Quantized Training library.
• array-api-compat — A wrapper around NumPy and other array libraries to make them compatible with the Array API standard
• array-api-jax-compat — Array-API JAX compatibility
• astax — A Jax based neural network library for research
• AttentionGrid — AttentionGrid - Library
• augmax — Efficiently Composable Data Augmentation on the GPU with Jax
• auto-uncertainties — Linear Uncertainty Propagation with Auto-Differentiation
• autobound — no summary
• autodiscjax — python library built on top of jax to facilitate automated exploration and simulation of computational models of biological processes
• autodyn — Differentiable Dynamical Systems
• AutoEis — A tool for automated EIS analysis by proposing statistically plausible ECMs.
• avici — Amortized Inference for Causal Structure Learning
• awblib — A bunch of Automatic White-Balancing (AWB) Algorithm implementations
• axlearn — AXLearn
• bambi — BAyesian Model Building Interface in Python
• bartz — A JAX implementation of BART
• BaSiCpy — A python package for background and shading correction of optical microscopy images
• bax — A flexible trainer interface for Jax and Haiku.
• bayes-jones — Bayesian inference of Jones matrices.
• BayesComBat — Fully Bayesian ComBat Harmonization
• bayesian-models — A package for building common bayesian models in pymc
• BayesMBAR — Bayesian Multistate Bennett Acceptance Ratio Methods
• bayesn — Hierarchical Bayesian modelling of type Ia SNe
• bayesnf — Scalable spatiotemporal prediction with Bayesian neural fields
• bayeux-ml — Stitching together probabilistic models and inference.
• bayex — Minimal Bayesian Optimization Implementation with Gaussian Processes written in JAX.
• bbhamux — Minimal library to construct Hierarchical Associative Memories
• bbo-calibcam — Calibrate intrinsic and extrinsic parameters of cameras with charuco boards
• benchmark-mi — Estimators of mutual information and distributions used to benchmark them.
• benchmarx — Tools for benchmarking optimization methods
• bfbrain — Use active learning to determine the bounded-from-below region in parameter space of a multiscalar potential in quantum field theory.
• blackjax — Flexible and fast sampling in Python
• blackjax-nightly — Flexible and fast sampling in Python
• bmr4pml — Bayesian model reduction for probabilistic machine learning
• boax — Boax is a Bayesian Optimization library for JAX.
• bobbin — Tools for making training loops with flax.linen models.
• bojaxns — Bayesian Optimisation with JAXNS
• bottleneck-transformer-flax — Bottleneck Transformer - Flax
• Brain-Py — BrainPy: Brain Dynamics Programming in Python
• braincore — The Core System for General-purpose Brain Dynamics Programming Framework.
• brainpy — BrainPy: Brain Dynamics Programming in Python
• brainpy.core — The core system for BrainPy programming framework.
• brainpy-largescale — brainpy-largescale depends on brainpy
• brainpylib-test — C++/CUDA Library for BrainPy
• braintools — The Toolbox for Brain Dynamics Programming.
• brax — A differentiable physics engine written in JAX.
• brax-jumpy — Common backend for JAX or numpy.
• brioche-enrichment — Bayesian tests for set enrichment.
• BSTPP — Bayesian Spatiotemporal Point Process
• bsts — Python library for Bayesian structural time series
• budoux — BudouX is the successor of Budou
• calcgp — Gaussian Process Regression framework for numerical integration and differentiation
• cascades — no summary
• casus — no summary
• catenets — Conditional Average Treatment Effect Estimation Using Neural Networks
• caujax — Causal Jax
• causal-discovery — no summary
• cca-zoo — Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework
• celerite2 — Fast and scalable Gaussian Processes in 1D
• cellrank — CellRank: dynamics from multi-view single-cell data
• ceml — Counterfactuals for explaining machine learning models - A Python toolbox
• cfnet — A counterfactual explanation library using Jax
• cfrx — Counterfactual Regret Minimization in Jax
• chemise — Wrapper for training flax models
• chemtrain — Training molecular dynamics potentials.
• chex — Chex: Testing made fun, in JAX!
• chimera-gw — Combined Hierarchical Inference Model for Electromagnetic and gRavitational-wave Analysis
• chromatix — Differentiable computational optics library using JAX!
• chromax — Breeding simulator based on JAX
• ciclo — no summary
• cleanrl — High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features
• cleverhans — no summary