GoMLX: An Accelerated Machine Learning Framework For Go
-
Updated
Dec 17, 2025 - Go
GoMLX: An Accelerated Machine Learning Framework For Go
Easy to use and blazing fast JAX-based library for high-performance 2D/3D Discrete Element Method (DEM) simulations.
S + Autograd + XLA :: S-parameter based frequency domain circuit simulations and optimizations using JAX.
Elegant and Performant Deep Learning
Enabling PyTorch on XLA Devices (e.g. Google TPU)
Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python ⚡
Repository of Computer Vision projects based on CNNs, Vision Transformers, and YOLO11, implemented with TensorFlow, PyTorch, Hugging Face, and Ultralytics.
A fast transfer matrix method written in jax for modelling optical multilayer thin films
Experimentation using the xla compiler from rust
JAX Foreign Function Interface experiments
JAX - A curated list of resources https://github.com/google/jax
katmer is a powerful library for optimizing the design of optical thin films using automatic differentiation via JAX and Equinox, enabling efficient and accurate inverse design solutions.
Add a description, image, and links to the xla topic page so that developers can more easily learn about it.
To associate your repository with the xla topic, visit your repo's landing page and select "manage topics."