Optimizing Drug Design by Merging Generative AI With Active Learning Frameworks. - Isaac Filella-Merce; Alexis Molina; Marek Orzechowski; Lucía Díaz; Yang Ming Zhu; Julia Vilalta Mor; Laura Malo; Ajay S. Yekkirala; Soumya S. Ray; Victor Guallar (CoRR, 2023)

GeoDirDock: Guiding Docking Along Geodesic Paths. - Raúl Miñán; Javier Gallardo; Álvaro Ciudad; Alexis Molina (CoRR, 2024)

Are Protein Language Models Compute Optimal? - Yaiza Serrano; Álvaro Ciudad; Alexis Molina (CoRR, 2024)

Scoreformer: A Surrogate Model For Large-Scale Prediction of Docking Scores. - Álvaro Ciudad; Adrián Morales-Pastor; Laura Malo; Isaac Filella-Merce; Victor Guallar; Alexis Molina (CoRR, 2024)

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. - Guillermo Bernárdez; Lev Telyatnikov; Marco Montagna; Federica Baccini; Mathilde Papillon; Miquel Ferriol Galmés; Mustafa Hajij; Theodore Papamarkou; Maria Sofia Bucarelli; Olga Zaghen; Johan Mathe; Audun Myers; et al. (CoRR, 2024)

Character-level Tokenizations as Powerful Inductive Biases for RNA Foundational Models. - Adrián Morales-Pastor; Raquel Vázquez-Reza; Milosz Wieczór; Clàudia Valverde; Manel Gil-Sorribes; Bertran Miquel-Oliver; Álvaro Ciudad; Alexis Molina (CoRR, 2024)

Addressing Model Overcomplexity in Drug-Drug Interaction Prediction With Molecular Fingerprints. - Manel Gil-Sorribes; Alexis Molina (CoRR, 2025)

sHGCN: Simplified hyperbolic graph convolutional neural networks. - Pol Arévalo; Alexis Molina; Álvaro Ciudad (CoRR, 2025)

Active Learning-Guided Seq2Seq Variational Autoencoder for Multi-target Inhibitor Generation. - Julia Vilalta Mor; Alexis Molina; Laura Ortega Varga; Isaac Filella-Merce; Victor Guallar (CoRR, 2025)