5 papers
Hyper-Dimensional Fingerprints as Molecular Representations
Jonas Teufel, Luca Torresi, André Eberhard +1
Computational molecular representations underpin virtual screening, property prediction, and materials discovery. Conventional fingerprints are efficient and deterministic but lose…
Generative Models for Crystalline Materials
Houssam Metni, Laura Ruple, Lauren N. Walters +13
Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has eme…
Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI
Hunter Sturm, Jonas Teufel, Kaitlin A. Isfeld +2
Herein, we present the application of MEGAN, our explainable AI (xAI) model, for the identification of small colloidally aggregating molecules (SCAMs). This work offers solutions t…
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification
Jonas Teufel, Annika Leinweber, Pascal Friederich
Explainable AI (xAI) interventions aim to improve interpretability for complex black-box models, not only to improve user trust but also as a means to extract scientific insights f…
opXRD: Open Experimental Powder X-ray Diffraction Database
Daniel Hollarek, Henrik Schopmans, Jona Ãstreicher +21
Powder X-ray diffraction (pXRD) experiments are a cornerstone for materials structure characterization. Despite their widespread application, analyzing pXRD diffractograms still pr…