3 papers
cs.LG2022
Unity Smoothing for Handling Inconsistent Evidence in Bayesian Networks and Unity Propagation for Faster Inference
Mads Lindskou, Torben Tvedebrink, Poul Svante Eriksen +2
We propose Unity Smoothing (US) for handling inconsistencies between a Bayesian network model and new unseen observations. We show that prediction accuracy, using the junction tree…
stat.CO2021
sparta: Sparse Tables and their Algebra with a View Towards High Dimensional Graphical Models
Mads Lindskou, Søren Højsgaard, Poul Svante Eriksen +1
A graphical model is a multivariate (potentially very high dimensional) probabilistic model, which is formed by combining lower dimensional components. Inference (computation of co…
math.ST2021
Detecting Outliers in High-dimensional Data with Mixed Variable Types using Conditional Gaussian Regression Models
Mads Lindskou, Torben Tvedebrink, Poul Svante Eriksen +1
Outlier detection has gained increasing interest in recent years, due to newly emerging technologies and the huge amount of high-dimensional data that are now available. Outlier de…