Reverse Dependencies of distrax
The following projects have a declared dependency on distrax:
- ARLBench — Python Boilerplate that contains all the code you need to create a Python package.
- craftax — An open-world environment for training RL agents
- dopamax — Reinforcement learning in pure JAX.
- flashbax — Flashbax is an experience replay library oriented around JAX. Tailored to integrate seamlessly with JAX's Just-In-Time (JIT) compilation.
- fusions — Diffusion meets sampling
- gpjax-nightly — Didactic Gaussian processes in Jax.
- harmonic — Python package for efficient Bayesian evidence computation
- jaxagents — JAX implementation of Reinforcement Learning agents
- jaxfss — JAX/Flax implementation of finite-size scaling
- jaxkern-nightly — Kernels in Jax.
- jaxmarl — Multi-Agent Reinforcement Learning with JAX
- JaxUtils — Utility functions for JaxGaussianProcesses
- jaxutils-nightly — Utility functions for JaxGaussianProcesses
- kfac-jax — A Jax package for approximate curvature estimation and optimization using KFAC.
- metrx — "A library containing a collection of distance and similarity measures to compare time series data."
- modularbayes — Modular Bayesian Inference.
- MOGPJax — Didactic multi-output Gaussian processes in Jax.
- momaland — A standard API for Multi-Objective Multi-Agent Decision making and a diverse set of reference environments.
- probabilistic-reconciliation — Probabilistic reconciliation of time series forecasts
- queuinx — Queuinx: A library for performance evaluation in Jax
- rejax — Vectorizable RL algorithms in pure JAX
- rex-lib — Robotic Environments with jaX (REX)
- rlax — A library of reinforcement learning building blocks in JAX.
- robo-transformers — RT-1, RT-1-X, Octo Robotics Transformer Model Inference
- sbijax — Simulation-based inference in JAX
- softclip — JAX/Flax implementation of softclip
- surjectors — Surjection layers for density estimation with normalizing flows
- synthetic-gymnax — Synthetic gymnax environments
- xminigrid — JAX-accelerated meta-reinforcement learning environments inspired by XLand and MiniGrid
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