Selectivity profiling of BCRP versus P-gp inhibition: from automated collection of polypharmacology data to multi-label learning. - Floriane Montanari; Barbara Zdrazil; Daniela Digles; Gerhard F. Ecker (J. Cheminformatics, 2016)

Gini in a Bottleneck: Gotta Train Me the Right Way. - Ryan Henderson; Djork-Arné Clevert; Floriane Montanari (CoRR, 2020)

Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity. - Ryan Henderson; Djork-Arné Clevert; Floriane Montanari (ICML, 2021)

ChemInformatics Model Explorer (CIME): exploratory analysis of chemical model explanations. - Christina Humer; Henry Heberle; Floriane Montanari; Thomas Wolf; Florian Huber; Ryan Henderson; Julian Heinrich; Marc Streit (J. Cheminformatics, 2022)

Explaining, Evaluating and Enhancing Neural Networks' Learned Representations. - Marco Bertolini; Djork-Arné Clevert; Floriane Montanari (ICANN (5), 2023)

From slides (through tiles) to pixels: an explainability framework for weakly supervised models in pre-clinical pathology. - Marco Bertolini; Van-Khoa Le; Jake Pencharz; Andreas Poehlmann; Djork-Arné Clevert; Santiago Villalba; Floriane Montanari (CoRR, 2023)

pH-dependent solubility prediction for optimized drug absorption and compound uptake by plants. - Anne Bonin; Floriane Montanari; Sebastian Niederführ; Andreas H. Göller (J. Comput. Aided Mol. Des., 2023)

Enhancing Interpretability in Molecular Property Prediction with Contextual Explanations of Molecular Graphical Depictions. - Marco Bertolini; Linlin Zhao; Floriane Montanari; Djork-Arné Clevert (AIDD@ICANN, 2024)