google / autoboundLinks
AutoBound automatically computes upper and lower bounds on functions.
☆361Updated last year
Alternatives and similar repositories for autobound
Users that are interested in autobound are comparing it to the libraries listed below
Sorting:
- Turn SymPy expressions into trainable JAX expressions.☆347Updated 4 months ago
- ☆247Updated last month
- Compositional Linear Algebra☆489Updated 3 weeks ago
- Mathematical operations for JAX pytrees☆200Updated 8 months ago
- Oryx is a library for probabilistic programming and deep learning built on top of Jax.☆275Updated this week
- Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax☆467Updated this week
- Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/☆463Updated last week
- Run PyTorch in JAX. 🤝☆277Updated last week
- Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python☆489Updated 3 weeks ago
- Hardware accelerated, batchable and differentiable optimizers in JAX.☆990Updated 4 months ago
- Orbax provides common checkpointing and persistence utilities for JAX users☆415Updated this week
- Extending JAX with custom C++ and CUDA code☆398Updated last year
- ☆875Updated 3 weeks ago
- Named Tensors for Legible Deep Learning in JAX☆201Updated this week
- OpTree: Optimized PyTree Utilities☆190Updated last week
- A Python package of computer vision models for the Equinox ecosystem.☆108Updated last year
- CLU lets you write beautiful training loops in JAX.☆355Updated 2 months ago
- PIX is an image processing library in JAX, for JAX.☆421Updated 5 months ago
- ☆584Updated last week
- Automatic gradient descent☆209Updated 2 years ago
- JAX Arrays for human consumption☆105Updated last month
- Library for reading and processing ML training data.☆505Updated this week
- Named tensors with first-class dimensions for PyTorch☆331Updated 2 years ago
- ☆209Updated last week
- Second Order Optimization and Curvature Estimation with K-FAC in JAX.☆282Updated last month
- A functional training loops library for JAX☆88Updated last year
- Multiple dispatch over abstract array types in JAX.☆128Updated this week
- MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvement…☆389Updated last week
- A pure-functional implementation of a machine learning transformer model in Python/JAX☆178Updated 3 months ago
- Universal Tensor Operations in Einstein-Inspired Notation for Python.☆399Updated 4 months ago