25 citations · 54 across the 9 of their papers we have counts for
10 papers
Shotgun DNA sequencing for human identification: Dynamic SNP selection and likelihood ratio calculations accounting for errors
Mikkel Meyer Andersen, Marie-Louise Kampmann, Alberte Honoré Jepsen +4
In forensic genetics, short tandem repeats (STRs) are used for human identification (HID). Degraded biological trace samples with low amounts of short DNA fragments (low-quality DN…
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…
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…
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…
DNA mixture deconvolution using an evolutionary algorithm with multiple populations, hill-climbing, and guided mutation
Søren B. Vilsen, Torben Tvedebrink, Poul Svante Eriksen
DNA samples crime cases analysed in forensic genetics, frequently contain DNA from multiple contributors. These occur as convolutions of the DNA profiles of the individual contribu…
Targeted Fused Ridge Estimation of Inverse Covariance Matrices from Multiple High-Dimensional Data Classes
Anders Ellern Bilgrau, Carel F. W. Peeters, Poul Svante Eriksen +2
We consider the problem of jointly estimating multiple inverse covariance matrices from high-dimensional data consisting of distinct classes. An -penalized maximum likeliho…