Reverse Dependencies of jaxlib

The following projects have a declared dependency on jaxlib:

• 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
• 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.
• ajents — RL agents in JAX
• 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.
• aqtp — Accurate Quantized Training library.
• array-api-jax-compat — Array-API JAX compatibility
• astax — A Jax based neural network library for research
• auto-uncertainties — Linear Uncertainty Propagation with Auto-Differentiation
• 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
• bayes-jones — Bayesian inference of Jones matrices.
• BayesComBat — Fully Bayesian ComBat Harmonization
• bayesian-models — A package for building common bayesian models in pymc
• bayex — Minimal Bayesian Optimization Implementation with Gaussian Processes written in JAX.
• bbo-calibcam — Calibrate intrinsic and extrinsic parameters of cameras with charuco boards
• benchmark-mi — Estimators of mutual information and distributions used to benchmark them.
• bio-embeddings — A pipeline for protein embedding generation and visualization
• blackjax — Flexible and fast sampling in Python
• blackjax-nightly — Flexible and fast sampling in Python
• boax — Boax is a Bayesian Optimization library for JAX.
• 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
• brainscale — The Scalable Online Learning Algorithm and Framework for Biological Spiking Neural Networks.
• braintools — The Toolbox for Brain Dynamics Programming.
• brax — A differentiable physics engine written in JAX.
• brax-jumpy — Common backend for JAX or numpy.
• BSTPP — Bayesian Spatiotemporal Point Process
• calcgp — Gaussian Process Regression framework for numerical integration and differentiation
• casus — no summary
• catenets — Conditional Average Treatment Effect Estimation Using Neural Networks
• causal-discovery — no summary
• celerite2 — Fast and scalable Gaussian Processes in 1D
• ceml — Counterfactuals for explaining machine learning models - A Python toolbox
• chex — Chex: Testing made fun, in 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
• clu — Set of libraries for ML training loops in JAX.
• coax — Plug-n-play reinforcement learning with Gymnasium and JAX
• coaxtract — Permittivity extraction from open-ended coaxial probe measurements
• codex-africanus — Radio Astronomy Building Blocks
• cody-adapter-transformers — A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models
• coffeegrinder — COFFEE is an MPI-Parallelised Python package for the numerical evolution of time-dependent differential equations.
• coix — Inference Combinators in JAX
• coltra — Coltra is a simple moddable RL algorithm implementation
• coltra-rl — Coltra-RL is a simple moddable RL algorithm implementation
• coola — A library to check if two complex/nested objects are equal or not
• coordinax — Vectors in JAX
• coppafish — coppaFISH software for Python
• correctionlib-gradients — Automatic differentiation for high-energy physics correction factor calculations.
• cortecs — Compress opacity for radiative transfer
• cpa-tools — Compositional Perturbation Autoencoder (CPA)
• cpwxtract — Permittivity extraction from open-ended coaxial probe measurements
• cr-nimble — Iterative algorithms for numerical linear algebra with JAX
• crikit — Constitutive Relation Inference Toolkit
• cryojax — Cryo-EM image simulation and analysis powered by JAX
• datasets — HuggingFace community-driven open-source library of datasets
• decayangle — A tool for wigner rotations in n-body decays
• deepchem — Deep learning models for drug discovery, quantum chemistry, and the life sciences.
• deeperwin — A JAX based framework to calculate deep-learning VMC solutions to the Schrödinger equation
• deepqmc — Deep-learning quantum Monte Carlo for electrons in real space
• dgenerate — Batch image generation and manipulation tool supporting Stable Diffusion and related techniques / algorithms, with support for video and animated image processing.
• dibs-lib — DiBS: Differentiable Bayesian Structure Learning
• diffjeom — Differential geometry with jax
• diffqc — Diiferentiable Quantum Simulator
• diffusers — State-of-the-art diffusion in PyTorch and JAX.
• diffusers-unchained — Diffusers
• diffusersv — State-of-the-art diffusion in PyTorch and JAX.
• discopy — The Python toolkit for computing with string diagrams.
• distrax — Distrax: Probability distributions in JAX.
• dkmri-WIN — Reproducible and efficient diffusion kurtosis imaging in Python.
• dks — A Python library implementing the DKS/TAT neural network transformation method.
• dLux — Differentiable Optical Models as Parameterised Neural Networks in Jax using Zodiax.
• dm-clrs — The CLRS Algorithmic Reasoning Benchmark.
• dm-haiku — Haiku is a library for building neural networks in JAX.
• dm-pix — PIX is an image processing library in JAX, for JAX.
• dMO — A package for learning cutting planes for mixed-integer optimization problems.
• dmol-book — Style and Imports for dmol Book