Reverse Dependencies of dm-haiku

The following projects have a declared dependency on dm-haiku:

• 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
• alphapulldown — Pipeline allows massive screening using alphafold
• avici — Amortized Inference for Causal Structure Learning
• bax — A flexible trainer interface for Jax and Haiku.
• bayes-jones — Bayesian inference of Jones matrices.
• catx — Contextual Bandits with Continuous Actions in JAX
• causal-discovery — no summary
• cfnet — A counterfactual explanation library using Jax
• chemtrain — Training molecular dynamics potentials.
• coax — Plug-n-play reinforcement learning with Gymnasium and JAX
• colabfold — Making protein folding accessible to all. Predict proteins structures both in google colab and on your machine
• declearn — Declearn - a python package for private decentralized learning.
• deepchem — Deep learning models for drug discovery, quantum chemistry, and the life sciences.
• deepqmc — Deep-learning quantum Monte Carlo for electrons in real space
• dks — A Python library implementing the DKS/TAT neural network transformation method.
• dm-clrs — The CLRS Algorithmic Reasoning Benchmark.
• dmol-book — Style and Imports for dmol Book
• dopamax — Reinforcement learning in pure JAX.
• e3nn-jax — Equivariant convolutional neural networks for the group E(3) of 3 dimensional rotations, translations, and mirrors.
• egnn-jax — E(3) GNN in jax
• explainax — JAX-based Model Explanation and Interpretation Library
• 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.
• 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.
• flashbax — Flashbax is an experience replay library oriented around JAX. Tailored to integrate seamlessly with JAX's Just-In-Time (JIT) compilation.
• gpax — Gaussian processes in NumPyro and JAX
• haiku-geometric — no summary
• haiku-mup — A simple port of μP to Haiku/JAX.
• hijax — An experiment framework for Haiku and Jax
• jax-cfd — no summary
• jax-dataloader — Dataloader for jax
• jax-dimenet — DimeNet++ in Jax.
• jax-dips — Differentiable 3D interfacial PDE solvers written in JAX using the Neural Bootstrapping Method.
• jax-md — Differentiable, Hardware Accelerated, Molecular Dynamics
• jax-relax — JAX-based Recourse Explanation Library
• jax-toolkit — A collection of jax functions to help with common machine/deep learning related functionality.
• jax-verify — A library for neural network verification.
• jaxex — A tool for creating science experiments in jax, torch, brax, etc
• jaxns — Nested Sampling in JAX
• jaxrie — Riemannian JAX
• jraph — Jraph: A library for Graph Neural Networks in Jax
• jumanji — A diverse suite of scalable reinforcement learning environments in JAX
• juxtapose — no summary
• kagglefold — Making protein folding accessible in kaggle platform
• kfac-jax — A Jax package for approximate curvature estimation and optimization using KFAC.
• lagrangebench — LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite
• learned-optimization — Train learned optimizers in Jax.
• mlp-gpt-jax — MLP GPT - Jax
• modularbayes — Modular Bayesian Inference.
• moss-rl — A Python library for Reinforcement Learning.
• muax — A library written in Jax that provides help for using DeepMind's mctx on gym-style environments.
• mubelnet — Deep Bayesian unsupervised decoder networks. Use poisson or multinomial belief networks to cluster non-negative count data.
• nndp — Dynamic Programming using Neural Networks
• non-param-score-est — Non parametric score function estimation library
• numpyro — Pyro PPL on NumPy
• pandas-toolkit — A collection of pandas accessors to help with common machine/deep learning related functionality.
• pax3 — A stateful pytree library for training neural networks.
• progen-transformer — Protein Generation (ProGen)
• pyRDDLGym-jax — pyRDDLGym-jax: JAX compilation of RDDL description files, and a differentiable planner in JAX.
• rljax — A collection of RL algorithms written in JAX.
• safejax — Serialize JAX, Flax, Haiku, or Objax model params with `safetensors`
• sbijax — Simulation-based inference in JAX
• segnn-jax — Steerable E(3) GNN in jax
• spyx — Spyx: SNNs in JAX
• surjectors — Surjection layers for density estimation with normalizing flows
• syft — Perform numpy-like analysis on data that remains in someone elses server
• synecdoche — Synecdoche: Hypernetworks for Haiku in JAX
• tracr-pypi — Compiler from RASP to transformer weights
• tsuite — tsuite: Get your RL agent fixed today!
• wax-ml — A Python library for machine-learning and feedback loops on streaming data
• wazy — Pretrained Bayesian Optimization of Sequences
• x-mlps — Configurable MLPs built on JAX and Haiku
• xpag — xpag: Exploring Agents