Reverse Dependencies of optax

The following projects have a declared dependency on optax:

• acni — A Jax/Optax implementation of Anticorrelated Noise Injection for Improved Generalization
• ai2-tango — A library for choreographing your machine learning research.
• apax — Atomistic Learned Potential Package in JAX
• autodiscjax — python library built on top of jax to facilitate automated exploration and simulation of computational models of biological processes
• avici — Amortized Inference for Causal Structure Learning
• aws-fortuna — A Library for Uncertainty Quantification.
• axlearn — AXLearn
• bax — A flexible trainer interface for Jax and Haiku.
• bayes-jones — Bayesian inference of Jones matrices.
• BayesMBAR — Bayesian Multistate Bennett Acceptance Ratio Methods
• bayesnf — Scalable spatiotemporal prediction with Bayesian neural fields
• bayeux-ml — Stitching together probabilistic models and inference.
• benchmark-mi — Estimators of mutual information and distributions used to benchmark them.
• best-package — no summary
• 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.
• brax — A differentiable physics engine written in JAX.
• catalax — A JAX-based framework for (neural) ODE modelling in biocatalysis.
• catx — Contextual Bandits with Continuous Actions in JAX
• causal-discovery — no summary
• cfnet — A counterfactual explanation library using Jax
• chemtrain — Training molecular dynamics potentials.
• clax — Prebuilt jax classifiers
• clip-jax — Training of CLIP in JAX
• coax — Plug-n-play reinforcement learning with Gymnasium and JAX
• cody-adapter-transformers — A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models
• coix — Inference Combinators in JAX
• coreax — Jax coreset algorithms.
• craftax — An open-world environment for training RL agents
• crispio — Designing CRISPR-Cas guide RNAs in bacteria.
• cupbearer — A library for mechanistic anomaly detection
• dalle-mini — DALL·E mini - Generate images from a text prompt
• deepchem — Deep learning models for drug discovery, quantum chemistry, and the life sciences.
• deepqmc — Deep-learning quantum Monte Carlo for electrons in real space
• deluca — no summary
• dgenerate — Batch image generation and manipulation tool supporting Stable Diffusion and related techniques / algorithms, with support for video and animated image processing.
• dgmrf — Deep Gaussian Markov Random Fields and their extensions
• differt — Differentiable Ray Tracing Toolbox for Radio Propagation Simulations
• DiffeRT2d — 2D Toolbox for Differentiable Ray Tracing
• diffqc — Diiferentiable Quantum Simulator
• dinf — discriminator-based inference for population genetics
• discco — Quantification of membrane and cytoplasmic concentrations based on differentiable simulation of cell cortex images
• dm-clrs — The CLRS Algorithmic Reasoning Benchmark.
• dMO — A package for learning cutting planes for mixed-integer optimization problems.
• dopamax — Reinforcement learning in pure JAX.
• dynamax — Dynamic State Space Models in JAX.
• e3nn-jax — Equivariant convolutional neural networks for the group E(3) of 3 dimensional rotations, translations, and mirrors.
• EasyDeL — An open-source library to make training faster and more optimized in Jax/Flax
• egnn-jax — E(3) GNN in jax
• emlp — A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
• eqxvision — Root package info.
• evermore — Differentiable (binned) likelihoods in JAX.
• evox — evox
• explainax — JAX-based Model Explanation and Interpretation Library
• f3dasm-optimize — f3dasm_optimize: Your one line description of the package
• fastreg — Fast sparse regressions
• fedjax — Federated learning simulation with JAX.
• fedml-afaf — A research and production integrated edge-cloud library for federated/distributed machine learning at anywhere at any scale.
• feedbax — Optimal feedback control + interventions in JAX.
• femr-cuda — Framework for Electronic Medical Records. A python package for building models using EHR data.
• femr-oldcpu — Framework for Electronic Medical Records. A python package for building models using EHR data.
• fjformer — Embark on a journey of paralleled/unparalleled computational prowess with FJFormer - an arsenal of custom Jax Flax Functions and Utils that elevate your AI endeavors to new heights!
• flashbax — Flashbax is an experience replay library oriented around JAX. Tailored to integrate seamlessly with JAX's Just-In-Time (JIT) compilation.
• flax — Flax: A neural network library for JAX designed for flexibility
• flax-trainer — Flax Trainer
• flaxsr — Super Resolution tools with Jax/Flax
• flowjax — Easy to use distributions, bijections and normalizing flows in JAX.
• flowMC — Normalizing flow exhanced sampler in jax
• fouriax — A jax port of auraloss
• galilei — the galilei project.
• generax — Generative Models using Jax
• gigalens — Fast strong gravitational lens modeling
• git-t5 — Open source machine learning framework for training T5 models on source code in JAX/Flax.
• google-vizier — Open Source Vizier: Distributed service framework for blackbox optimization and research.
• google-vizier-dev — Open Source Vizier: Distributed service framework for blackbox optimization and research.
• gpfy — Gaussian process with spherical harmonic features in JAX
• GPJax — Gaussian processes in JAX.
• gpjax-nightly — Didactic Gaussian processes in Jax.
• graphiq — GraphiQ is a Python library for the simulation, design, and optimization of quantum photonic circuits.
• gsmvi — Implementation of Gaussian score matching for variational inference (arXiv:2307.07849)
• gtech-optimus — Optimus library for real-time marketing personalization using RL.
• haiku-mup — A simple port of μP to Haiku/JAX.
• halospec — Halo Spectroscopy for JWST/MIRI
• Helx — Interoperate among reinforcement learning libraries with jax, pytorch, gym and dm_env
• Helx-agents — Interoperate among reinforcement learning libraries with jax, pytorch, gym and dm_env
• hijax — An experiment framework for Haiku and Jax
• horqrux — Jax-based quantum state vector simulator.
• hubblax — Simulating Transient in the sky and how to observe them
• hypercoil — Differentiable programming for neuroimaging analysis
• icomo — This toolbox aims to simplify the construction of compartmental models and the inference of their parameters
• invrs-gym — A collection of inverse design challenges
• jax-dataloader — Dataloader for jax
• jax-dips — Differentiable 3D interfacial PDE solvers written in JAX using the Neural Bootstrapping Method.
• jax-jynx — A neural network library using jax
• jax-md — Differentiable, Hardware Accelerated, Molecular Dynamics
• jax-metrics — no summary
• jax-nca — Neural Cellular Automata (https://distill.pub/2020/growing-ca/ -- Mordvintsev, et al., "Growing Neural Cellular Automata", Distill, 2020) implemented in JAX
• jax-nerf — Jax implementation of neural radiance fields