Macau: Scalable Bayesian factorization with high-dimensional side information using MCMC. - Jaak Simm; Adam Arany; Pooya Zakeri; Tom Haber; Jörg K. Wegner; Vladimir I. Chupakhin; Hugo Ceulemans; Yves Moreau (MLSP, 2017)

Scaling machine learning for target prediction in drug discovery using Apache Spark. - Dries Harnie; Mathijs Saey; Alexander E. Vapirev; Jörg Kurt Wegner; Andrey Gedich; Marvin N. Steijaert; Hugo Ceulemans; Roel Wuyts; Wolfgang De Meuter (Future Gener. Comput. Syst., 2017)

ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. - Jiangming Sun; Nina Jeliazkova; Vladimir I. Chupakhin; José Felipe Golib Dzib; Ola Engkvist; Lars Carlsson; Jörg K. Wegner; Hugo Ceulemans; Ivan Georgiev; Vedrin Jeliazkov; Nikolay T. Kochev; Thomas J. Ashby; et al. (J. Cheminformatics, 2017)

Erratum to: ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. - Jiangming Sun; Nina Jeliazkova; Vladimir I. Chupakhin; José Felipe Golib Dzib; Ola Engkvist; Lars Carlsson; Jörg K. Wegner; Hugo Ceulemans; Ivan Georgiev; Vedrin Jeliazkov; Nikolay T. Kochev; Thomas J. Ashby; et al. (J. Cheminformatics, 2017)

SMURFF: A High-Performance Framework for Matrix Factorization Methods. - Tom Vander Aa; Imen Chakroun; Tom Ashby; Jaak Simm; Adam Arany; Yves Moreau; Thanh Le Van; José Felipe Golib Dzib; Jörg K. Wegner; Vladimir I. Chupakhin; Hugo Ceulemans; Roel Wuyts; et al. (BNAIC/BENELEARN, 2019)

ExCAPE-DB: An Integrated Large Scale Dataset Facilitating Big Data Analysis in Chemogenomics. - Jiangming Sun; Nina Jeliazkova; Vladimir I. Chupakhin; José Felipe Golib Dzib; Lars Carlsson; Jörg K. Wegner; Hugo Ceulemans; Ivan Georgiev; Vedrin Jeliazkov; Nikolay T. Kochev; Thomas J. Ashby; Hongming Chen 001 (BNAIC/BENELEARN, 2019)

Fast semi-supervised discriminant analysis for binary classification of large data sets. - Joris Tavernier; Jaak Simm; Karl Meerbergen; Jörg Kurt Wegner; Hugo Ceulemans; Yves Moreau (Pattern Recognit., 2019)

Industry-scale application and evaluation of deep learning for drug target prediction. - Noé Sturm; Andreas Mayr; Thanh Le Van; Vladimir I. Chupakhin; Hugo Ceulemans; Jörg K. Wegner; José Felipe Golib Dzib; Nina Jeliazkova; Yves Vandriessche; Stanislav Böhm; Vojtech Cima; Jan Martinovic; et al. (J. Cheminformatics, 2020)

Industry-Scale Orchestrated Federated Learning for Drug Discovery. - Martijn Oldenhof; Gergely Ács; Balázs Pejó; Ansgar Schuffenhauer; Nicholas Holway; Noé Sturm; Arne Dieckmann; Oliver Fortmeier; Eric Boniface; Clément Mayer; Arnaud Gohier; Peter Schmidtke; et al. (CoRR, 2022)

Industry-Scale Orchestrated Federated Learning for Drug Discovery. - Martijn Oldenhof; Gergely Ács; Balázs Pejó; Ansgar Schuffenhauer; Nicholas Holway; Noé Sturm; Arne Dieckmann; Oliver Fortmeier; Eric Boniface; Clément Mayer; Arnaud Gohier; Peter Schmidtke; et al. (AAAI, 2023)

Balancing Imbalanced Toxicity Models: Using MolBERT with Focal Loss. - Muhammad Arslan Masood; Samuel Kaski; Hugo Ceulemans; Dorota Herman; Markus Heinonen (AIDD@ICANN, 2024)

MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information. - Wouter Heyndrickx; Lewis H. Mervin; Tobias Morawietz; Noé Sturm; Lukas Friedrich; Adam Zalewski; Anastasia Pentina; Lina Humbeck; Martijn Oldenhof; Ritsuya Niwayama; Peter Schmidtke; Nikolas Fechner; et al. (J. Chem. Inf. Model., 2024)

Improving route development using convergent retrosynthesis planning. - Paula Torren-Peraire; Jonas Verhoeven; Dorota Herman; Hugo Ceulemans; Igor V. Tetko; Jörg K. Wegner (J. Cheminformatics, 2025)