Fast Parallel Exact Inference on Bayesian Networks: Poster

12/08/2022
by   Jiantong Jiang, et al.
0

Bayesian networks (BNs) are attractive, because they are graphical and interpretable machine learning models. However, exact inference on BNs is time-consuming, especially for complex problems. To improve the efficiency, we propose a fast BN exact inference solution named Fast-BNI on multi-core CPUs. Fast-BNI enhances the efficiency of exact inference through hybrid parallelism that tightly integrates coarse- and fine-grained parallelism. We also propose techniques to further simplify the bottleneck operations of BN exact inference. Fast-BNI source code is freely available at https://github.com/jjiantong/FastBN.

READ FULL TEXT

page 1

page 2

research
12/08/2022

Fast Parallel Bayesian Network Structure Learning

Bayesian networks (BNs) are a widely used graphical model in machine lea...
research
04/17/2023

pgmpy: A Python Toolkit for Bayesian Networks

Bayesian Networks (BNs) are used in various fields for modeling, predict...
research
11/01/2022

Efficient AlphaFold2 Training using Parallel Evoformer and Branch Parallelism

The accuracy of AlphaFold2, a frontier end-to-end structure prediction s...
research
04/21/2018

A Channel-based Exact Inference Algorithm for Bayesian Networks

This paper describes a new algorithm for exact Bayesian inference that i...
research
08/16/2019

daBNN: A Super Fast Inference Framework for Binary Neural Networks on ARM devices

It is always well believed that Binary Neural Networks (BNNs) could dras...
research
04/27/2018

Improving Coverage and Runtime Complexity for Exact Inference in Non-Projective Transition-Based Dependency Parsers

We generalize Cohen, Gómez-Rodríguez, and Satta's (2011) parser to a fam...
research
08/22/2019

Exact inference under the perfect phylogeny model

Motivation: Many inference tools use the Perfect Phylogeny Model (PPM) t...

Please sign up or login with your details

Forgot password? Click here to reset