Transfer Learning for Predictive Models in Massive Open Online Courses. - Sebastien Boyer; Kalyan Veeramachaneni (AIED, 2015)

Data science foundry for MOOCs. - Sebastien Boyer; Ben U. Gelman; Benjamin Schreck; Kalyan Veeramachaneni (DSAA, 2015)

Robust Predictive Models on MOOCs : Transferring Knowledge across Courses. - Sebastien Boyer; Kalyan Veeramachaneni (EDM, 2016)

DropoutSeer: Visualizing learning patterns in Massive Open Online Courses for dropout reasoning and prediction. - Yuanzhe Chen; Qing Chen 001; Mingqian Zhao; Sebastien Boyer; Kalyan Veeramachaneni; Huamin Qu (VAST, 2016)

Parameters and determinants of responses to selection in antibody libraries. - Steven Schulz; Sebastien Boyer; Matteo Smerlak; Simona Cocco; Rémi Monasson; Clément Nizak; Olivier Rivoire (PLoS Comput. Biol., 2021)

Predicting protein stability changes under multiple amino acid substitutions using equivariant graph neural networks. - Sebastien Boyer; Sam Money-Kyrle; Oliver Bent (CoRR, 2023)

Protein binding affinity prediction under multiple substitutions applying eGNNs on Residue and Atomic graphs combined with Language model information: eGRAL. - Arturo Fiorellini-Bernardis; Sebastien Boyer; Christoph Brunken; Bakary N'tji Diallo; Karim Beguir; Nicolás López Carranza; Oliver Bent (CoRR, 2024)

Universally applicable and tunable graph-based coarse-graining for Machine learning force fields. - Christoph Brunken; Sebastien Boyer; Mustafa Omar; Martin Maarand; Olivier Peltre; Solal Attias; Bakary N'tji Diallo; Anastasia Markina; Olaf Othersen; Oliver Bent (CoRR, 2025)