1 citations · 1 across the 4 of their papers we have counts for
4 papers
When should we trust the annotation? Selective prediction for molecular structure retrieval from mass spectra
Mira Jürgens, Gaetan De Waele, Morteza Rakhshaninejad +1
Machine learning methods for identifying molecular structures from tandem mass spectra (MS/MS) have advanced rapidly, yet current approaches still exhibit significant error rates.…
Conformal Prediction for Uncertainty Estimation in Drug-Target Interaction Prediction
Morteza Rakhshaninejad, Mira Jurgens, Nicolas Dewolf +1
Accurate drug-target interaction (DTI) prediction with machine learning models is essential for drug discovery. Such models should also provide a credible representation of their u…
A calibration test for evaluating set-based epistemic uncertainty representations
Mira Jürgens, Thomas Mortier, Eyke Hüllermeier +2
The accurate representation of epistemic uncertainty is a challenging yet essential task in machine learning. A widely used representation corresponds to convex sets of probabilist…
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?
Mira Jürgens, Nis Meinert, Viktor Bengs +2
Trustworthy ML systems should not only return accurate predictions, but also a reliable representation of their uncertainty. Bayesian methods are commonly used to quantify both ale…