diff --git a/README.md b/README.md index 22b7627..5da380f 100644 --- a/README.md +++ b/README.md @@ -41,32 +41,21 @@ Available at [https://docs.kidger.site/jaxtyping](https://docs.kidger.site/jaxty ## See also: other libraries in the JAX ecosystem -#### Always useful - -[Equinox](https://github.com/patrick-kidger/equinox): neural networks and everything not already in core JAX! - -#### Deep learning - -[Optax](https://github.com/deepmind/optax): first-order gradient (SGD, Adam, ...) optimisers. - -[Orbax](https://github.com/google/orbax): checkpointing (async/multi-host/multi-device). - -[Levanter](https://github.com/stanford-crfm/levanter): scalable+reliable training of foundation models (e.g. LLMs). - -#### Scientific computing - -[Diffrax](https://github.com/patrick-kidger/diffrax): numerical differential equation solvers. - -[Optimistix](https://github.com/patrick-kidger/optimistix): root finding, minimisation, fixed points, and least squares. - -[Lineax](https://github.com/patrick-kidger/lineax): linear solvers. - -[BlackJAX](https://github.com/blackjax-devs/blackjax): probabilistic+Bayesian sampling. - -[sympy2jax](https://github.com/patrick-kidger/sympy2jax): SymPy<->JAX conversion; train symbolic expressions via gradient descent. - -[PySR](https://github.com/milesCranmer/PySR): symbolic regression. (Non-JAX honourable mention!) - -#### Awesome JAX - -[Awesome JAX](https://github.com/n2cholas/awesome-jax): a longer list of other JAX projects.## Finally +**Always useful** +[Equinox](https://github.com/patrick-kidger/equinox): neural networks and everything not already in core JAX! + +**Deep learning** +[Optax](https://github.com/deepmind/optax): first-order gradient (SGD, Adam, ...) optimisers. +[Orbax](https://github.com/google/orbax): checkpointing (async/multi-host/multi-device). +[Levanter](https://github.com/stanford-crfm/levanter): scalable+reliable training of foundation models (e.g. LLMs). + +**Scientific computing** +[Diffrax](https://github.com/patrick-kidger/diffrax): numerical differential equation solvers. +[Optimistix](https://github.com/patrick-kidger/optimistix): root finding, minimisation, fixed points, and least squares. +[Lineax](https://github.com/patrick-kidger/lineax): linear solvers. +[BlackJAX](https://github.com/blackjax-devs/blackjax): probabilistic+Bayesian sampling. +[sympy2jax](https://github.com/patrick-kidger/sympy2jax): SymPy<->JAX conversion; train symbolic expressions via gradient descent. +[PySR](https://github.com/milesCranmer/PySR): symbolic regression. (Non-JAX honourable mention!) + +**Awesome JAX** +[Awesome JAX](https://github.com/n2cholas/awesome-jax): a longer list of other JAX projects. diff --git a/docs/index.md b/docs/index.md index 1fea5ec..677ef7e 100644 --- a/docs/index.md +++ b/docs/index.md @@ -43,32 +43,21 @@ Have a read of the [Array annotations](./api/array.md) documentation on the left ## See also: other libraries in the JAX ecosystem -#### Always useful - -[Equinox](https://github.com/patrick-kidger/equinox): neural networks and everything not already in core JAX! - -#### Deep learning - -[Optax](https://github.com/deepmind/optax): first-order gradient (SGD, Adam, ...) optimisers. - -[Orbax](https://github.com/google/orbax): checkpointing (async/multi-host/multi-device). - -[Levanter](https://github.com/stanford-crfm/levanter): scalable+reliable training of foundation models (e.g. LLMs). - -#### Scientific computing - -[Diffrax](https://github.com/patrick-kidger/diffrax): numerical differential equation solvers. - -[Optimistix](https://github.com/patrick-kidger/optimistix): root finding, minimisation, fixed points, and least squares. - -[Lineax](https://github.com/patrick-kidger/lineax): linear solvers. - -[BlackJAX](https://github.com/blackjax-devs/blackjax): probabilistic+Bayesian sampling. - -[sympy2jax](https://github.com/patrick-kidger/sympy2jax): SymPy<->JAX conversion; train symbolic expressions via gradient descent. - -[PySR](https://github.com/milesCranmer/PySR): symbolic regression. (Non-JAX honourable mention!) - -#### Awesome JAX - -[Awesome JAX](https://github.com/n2cholas/awesome-jax): a longer list of other JAX projects.## Finally## See also: other libraries in the JAX ecosystem +**Always useful** +[Equinox](https://github.com/patrick-kidger/equinox): neural networks and everything not already in core JAX! + +**Deep learning** +[Optax](https://github.com/deepmind/optax): first-order gradient (SGD, Adam, ...) optimisers. +[Orbax](https://github.com/google/orbax): checkpointing (async/multi-host/multi-device). +[Levanter](https://github.com/stanford-crfm/levanter): scalable+reliable training of foundation models (e.g. LLMs). + +**Scientific computing** +[Diffrax](https://github.com/patrick-kidger/diffrax): numerical differential equation solvers. +[Optimistix](https://github.com/patrick-kidger/optimistix): root finding, minimisation, fixed points, and least squares. +[Lineax](https://github.com/patrick-kidger/lineax): linear solvers. +[BlackJAX](https://github.com/blackjax-devs/blackjax): probabilistic+Bayesian sampling. +[sympy2jax](https://github.com/patrick-kidger/sympy2jax): SymPy<->JAX conversion; train symbolic expressions via gradient descent. +[PySR](https://github.com/milesCranmer/PySR): symbolic regression. (Non-JAX honourable mention!) + +**Awesome JAX** +[Awesome JAX](https://github.com/n2cholas/awesome-jax): a longer list of other JAX projects.