jaxopt vs optimistix

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jaxopt		optimistix
	Project
1	Mentions	2
888	Stars	237
1.6%	Growth	-
7.8	Activity	8.5
2 days ago	Latest Commit	7 days ago
Python	Language	Python
Apache License 2.0	License	Apache License 2.0

The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

jaxopt

Posts with mentions or reviews of jaxopt. We have used some of these posts to build our list of alternatives and similar projects.

[P] JAXopt: Hardware accelerated (GPU/TPU), batchable and differentiable optimizers in JAX
1 project | /r/MachineLearning | 14 Jul 2021

optimistix

Posts with mentions or reviews of optimistix. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-14.

[P] Optimistix, nonlinear optimisation in JAX+Equinox!
3 projects | /r/MachineLearning | 14 Oct 2023

Hi everyone! I wanted to advertise my new JAX optimisation library Optimistix!
Show HN: Optimistix: Nonlinear Optimisation in Jax+Equinox
2 projects | news.ycombinator.com | 10 Oct 2023

What are some alternatives?

When comparing jaxopt and optimistix you can also consider the following projects:

jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

diffrax - Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

pyprobml - Python code for "Probabilistic Machine learning" book by Kevin Murphy

torchopt - TorchOpt is an efficient library for differentiable optimization built upon PyTorch.

datasets - TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...

PyNeuraLogic - PyNeuraLogic lets you use Python to create Differentiable Logic Programs

symbolicai - Compositional Differentiable Programming Library

pennylane - PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.