PGMax implements general factor graphs for discrete probabilistic graphical models (PGMs), and hardware-accelerated differentiable loopy belief propagation (LBP) in JAX.

2023年8月10日 · PGMax implements general factor graphs for discrete probabilistic graphical models (PGMs), and hardware-accelerated differentiable loopy belief propagation (LBP) in JAX.

PGMax is a library for working with Factor Graphs in JAX. It currently provides an interface for specifying factor graphs of any type, as well as an efficient implementation of max-product …

2022年2月8日 · PGMax is an open-source Python package for (a) easily specifying discrete Probabilistic Graphical Models (PGMs) as factor graphs; and (b) automatically running efficient …

2024年6月22日 · PGMax是一个强大的开源库，用于构建和解决离散概率图模型（PGMs）中的通用因子图问题。 它集成了硬件加速的可微分**循环信念传播（Loopy Belief Propagation, …

2024年9月12日 · pgmax/: 包含项目的主要代码文件，如 factor_graph.py 和 inference.py 等。 tests/ : 包含项目的测试代码文件，如 test_factor_graph.py 和 test_inference.py 等。 setup.py : …

We look forward to the new exciting research possibilities from PGMax's integration within DeepMind's rapidly growing JAX ecosystem. Loopy belief propagation for factor graphs on …

pgmax.infer.compute_energy (bp_state: pgmax.infer.bp_state.BPState, bp_arrays: pgmax.infer.bp_state.BPArrays, map_states: Dict [Hashable, Any], debug_mode = False) → …

Loopy belief propagation for factor graphs on discrete variables in JAX - google-deepmind/PGMax

2022年9月22日 · to install JAX for GPU. Here are a few self-contained Colab notebooks to help you get started on using PGMax. We recommend running them on GPU instances: PGMax is …