6 papers
ICON decomposition: Multivariate concept auditing reveals shortcuts that neural networks rely on
Roshan Prakash Rane, Marco Simnacher, Manuel Pfeuffer +7
Deep neural networks often exploit spurious associations, a failure known as shortcut learning. Before deployment, models should therefore be audited for reliance on concepts such…
Controlling for Omitted Variable Bias in Deep Neural Networks
Manuel Pfeuffer, Roshan Prakash Rane, Kerstin Ritter +1
Control variables are widely used in statistical modelling to account for omitted variable bias of known confounders. However, they have largely been underexplored in deep learning…
Interpreting Protein Language Model Embeddings via Orthogonal Projection for Protein Fitness Prediction
Paulo Yanez Sarmiento, Pia Francesca Rissom, Manuel Pfeuffer +6
Recently, there has been a growing adoption of protein language models (PLMs) in biomedical science. Their embeddings provide a rich numerical representation of protein sequences w…
Deep Shape Regression for Planar Curves with Multimodal Covariates
Manuel Pfeuffer, Roshan Prakash Rane, Hadya Yassin +2
The shape of a planar curve is the geometric information that remains once translation, rotation, scale and reparametrisation are removed and is of interest in many health applicat…
Better than Average: Spatially-Aware Aggregation of Segmentation Uncertainty Improves Downstream Performance
Vanessa Emanuela Guarino, Claudia Winklmayr, Jannik Franzen +7
Uncertainty Quantification (UQ) is crucial for ensuring the reliability of automated image segmentations in safety-critical domains like biomedical image analysis or autonomous dri…
Elastic Full Procrustes Analysis of Plane Curves via Hermitian Covariance Smoothing
Almond Stöcker, Manuel Pfeuffer, Lisa Steyer +1
Determining the mean shape of a collection of curves is not a trivial task, in particular when curves are only irregularly/sparsely sampled at discrete points. We newly propose an…