Search Results for author: Johan du Preez

Found 6 papers, 1 papers with code

A Probabilistic Graphical Model Approach to the Structure-and-Motion Problem

no code implementations7 Oct 2021 Simon Streicher, Willie Brink, Johan du Preez

We present a means of formulating and solving the well known structure-and-motion problem in computer vision with probabilistic graphical models.

Graph Coloring: Comparing Cluster Graphs to Factor Graphs

no code implementations5 Oct 2021 Simon Streicher, Johan du Preez

We present a means of formulating and solving graph coloring problems with probabilistic graphical models.

Strengthening Probabilistic Graphical Models: The Purge-and-merge Algorithm

1 code implementation30 Sep 2021 Simon Streicher, Johan du Preez

It is in principle possible to convert loopy PGMs to an equivalent tree structure, but this is usually impractical for interesting problems due to exponential blow-up.

Stabilising priors for robust Bayesian deep learning

no code implementations23 Oct 2019 Felix McGregor, Arnu Pretorius, Johan du Preez, Steve Kroon

Bayesian neural networks (BNNs) have developed into useful tools for probabilistic modelling due to recent advances in variational inference enabling large scale BNNs.

Variational Inference

The PAV algorithm optimizes binary proper scoring rules

no code implementations8 Apr 2013 Niko Brummer, Johan du Preez

There has been much recent interest in application of the pool-adjacent-violators (PAV) algorithm for the purpose of calibrating the probabilistic outputs of automatic pattern recognition and machine learning algorithms.

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