Reverse Dependencies of jaxtyping

The following projects have a declared dependency on jaxtyping:

• aigs — no summary
• alphafold3-pytorch — Alphafold 3 - Pytorch
• alphafold3-pytorch-lightning-hydra — AlphaFold 3 - Pytorch
• apax — Atomistic Learned Potential Package in JAX
• apebench — Benchmark suite for Autoregressive Neural Emulators of PDEs in JAX.
• arlatentsde — Amortized Reparametrization for Continuous Time Autoencoders (ARCTA)
• awblib — A bunch of Automatic White-Balancing (AWB) Algorithm implementations
• bayesian-lora — Bayesian LoRA adapters for Language Models
• bayesnf — Scalable spatiotemporal prediction with Bayesian neural fields
• bbhamux — Minimal library to construct Hierarchical Associative Memories
• beartype — Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.
• bqskit-qfactor-jax — QFactor GPU implementation in BQSKit using JAX
• breedgym — Suite of Gymnasium environments for optimizing breeding programs
• causal-validation — A validation framework for causal models.
• cfrx — Counterfactual Regret Minimization in Jax
• chai_lab — Chai Discovery tools for AI + protein research.
• chemise — Wrapper for training flax models
• chess-transformer — package_description
• chromax — Breeding simulator based on JAX
• cleosim — Cleo: the Closed-Loop, Electrophysiology, and Optogenetics experiment simulation testbed
• compress-em — Particle Picking of Cryo-EM Datasets
• coordinax — Coordinates in JAX
• coreax — Jax coreset algorithms.
• cryojax — Cryo-EM image simulation and analysis powered by JAX
• decoding — Composable inference algorithms with LLMs and programmable logic
• differt — Differentiable Ray Tracing Toolbox for Radio Propagation Simulations
• DiffeRT2d — 2D Toolbox for Differentiable Ray Tracing
• diffjpeg_jax — DiffJPEG implemented in JAX
• diffpose — Patient-specific intraoperative 2D/3D registration via differentiable rendering
• diffrax — GPU+autodiff-capable ODE/SDE/CDE solvers written in JAX.
• diffusionkit — Argmax Model Optimization Toolkit for Diffusion Models.
• distreqx — Lightweight JAX library of probability distributions and bijectors.
• dynamax — Dynamic State Space Models in JAX.
• dynamiqs — High-performance quantum systems simulation with JAX (GPU-accelerated & differentiable solvers).
• e2-tts-pytorch — E2-TTS in Pytorch
• e2e-sae — Repo for training sparse autoencoders end-to-end
• enzax — Differentiable models of enzyme-catalysed reaction networks
• equinox — Elegant easy-to-use neural networks in JAX.
• evermore — Differentiable (binned) likelihoods in JAX.
• exponax — Efficient differentiable PDE solvers in JAX.
• fastdev — Type less, code more
• feature-fabrica — Open-source Python library designed to improve engineering practices and transparency in feature engineering.
• feedbax — Optimal feedback control + interventions in JAX.
• fenbux — A Simple Statistical Distribution Library In JAX
• fiestaEM — Fast inference of electromagnetic signals with JAX
• flarejax — Flexible Neural Networks in JAX
• flarenet — Common neural network modules and utilities based on flarejax.
• flax — Flax: A neural network library for JAX designed for flexibility
• flowjax — Easy to use distributions, bijections and normalizing flows in JAX.
• folx — Forward Laplacian for JAX
• furax — Operators and solvers for high-performance computing.
• gatv2-eqx — Add your description here
• geometricjax-experimental — basic tests for full geometricjax library
• 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.
• gpytorch — An implementation of Gaussian Processes in Pytorch
• gradoptorch — Classical gradient based optimization in PyTorch
• grain — Grain: A library for loading and transforming data for neural network training.
• grain-nightly — Grain: A library for loading and transforming data for neural network training.
• graphein — Protein & Interactomic Graph Construction for Machine Learning
• gwkokab — A JAX-based gravitational-wave population inference
• haliax — Named Tensors for Legible Deep Learning in JAX
• infnum — Infinite and infinitesimal numbers for JAX
• inseq — Interpretability for Sequence Generation Models 🔍
• instanovo — De novo sequencing with InstaNovo
• janus-sim — A JAX Neural Simulator
• jax_chmc — An implementation of a family of MCMC methods on implicitly defined manifolds
• jax-f16 — Jax F16 dynamics
• jax-healpy — Healpix JAX implementation.
• jax-quantity — Quantities in JAX
• jax-russell — Financial options valuations and auto-diffed risk measures ("greeks" in Jax.
• jaxagents — JAX implementation of Reinforcement Learning agents
• jaxampler — A JAX-based statistical sampling toolkit
• jaxdecomp — JAX bindings for the cuDecomp library
• jaxfm — JAX-based implementation of Flow Matching
• jaximal — A JAX-based PyTree manipulation library
• JaxKern — Kernels in Jax.
• jaxkern-nightly — Kernels in Jax.
• jaxlem — LEM slope stability analysis using JAX
• jaxlinop-nightly — A JaxLinOp library.
• jaxonfunctions — Functions for JAX
• jaxonloader — A dataloader, but for JAX/Numpy
• jaxonmodels — JAX models for deep learning
• jaxparrow — Computes the inversion of the cyclogeostrophic balance based on a variational formulation approach, using JAX
• jaxrenderer — Jax implementation of rasterizer renderer.
• JaxUtils — Utility functions for JaxGaussianProcesses
• jaxutils-nightly — Utility functions for JaxGaussianProcesses
• jimGW — Gravitatioanl wave data analysis tool in Jax
• jit-env — A Jax interface for Reinforcement Learning environments.
• jnotype — Jnotype: probabilistic modeling of high-dimensional binary data.
• jo3mnist — no summary
• k-Wave-python — Acoustics toolbox for time domain acoustic and ultrasound simulations in complex and tissue-realistic media.
• kauldron — Kauldron is a ML research library optimized for quick iteration and modularity.
• keras-matmulless — Keras layers without using matrix multiplications.
• keras_sig — Path Signature in Pure Keras
• kira_llm — That's right, I'm Kira ✍️
• kiwi-mlutils — Misc machine learning utilities