google-deepmind / PGMaxLinks
Loopy belief propagation for factor graphs on discrete variables in JAX
☆154Updated 10 months ago
Alternatives and similar repositories for PGMax
Users that are interested in PGMax are comparing it to the libraries listed below
Sorting:
- Oryx is a library for probabilistic programming and deep learning built on top of Jax.☆275Updated this week
- JAX Arrays for human consumption☆105Updated last month
- Loopy belief propagation for factor graphs on discrete variables, in JAX!☆65Updated 10 months ago
- A Python package of computer vision models for the Equinox ecosystem.☆108Updated last year
- ☆247Updated last month
- ☆115Updated this week
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆235Updated last year
- A small library for creating and manipulating custom JAX Pytree classes☆56Updated 2 years ago
- This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.☆33Updated last year
- Minimal Implementation of Bayesian Optimization in JAX☆95Updated 4 months ago
- Turn SymPy expressions into trainable JAX expressions.☆347Updated 4 months ago
- Mathematical operations for JAX pytrees☆200Updated 8 months ago
- Add a tqdm progress bar to your JAX scans and loops.☆116Updated 3 months ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆100Updated 2 years ago
- Parameter-Free Optimizers for Pytorch☆130Updated last year
- Scalable training and inference for Probabilistic Circuits☆72Updated last month
- Compositional Linear Algebra☆489Updated 3 weeks ago
- Bayesian inference with Python and Jax.☆34Updated 2 years ago
- Pytorch-like dataloaders for JAX.☆94Updated 2 months ago
- Second Order Optimization and Curvature Estimation with K-FAC in JAX.☆282Updated last month
- A functional training loops library for JAX☆88Updated last year
- Run PyTorch in JAX. 🤝☆277Updated last week
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- Tools for JAX☆49Updated this week
- Riemannian Optimization Using JAX☆52Updated last year
- Multiple dispatch over abstract array types in JAX.☆128Updated this week
- Named Tensors for Legible Deep Learning in JAX☆201Updated this week
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆137Updated 2 months ago
- Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/☆463Updated last week
- Recursive Bayesian Estimation (Sequential / Online Inference)☆59Updated last year