Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - Dominique Beaini; Shenyang Huang; Joao Alex Cunha; Zhiyi Li; Gabriela Moisescu-Pareja; Oleksandr Dymov; Samuel Maddrell-Mander; Callum McLean; Frederik Wenkel; Luis Müller; Jama Hussein Mohamud; Ali Parviz; et al. (CoRR, 2023)

Role of Structural and Conformational Diversity for Machine Learning Potentials. - Nikhil Shenoy; Prudencio Tossou; Emmanuel Noutahi; Hadrien Mary; Dominique Beaini; Jiarui Ding (CoRR, 2023)

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - Dominique Beaini; Shenyang Huang; Joao Alex Cunha; Zhiyi Li; Gabriela Moisescu-Pareja; Oleksandr Dymov; Samuel Maddrell-Mander; Callum McLean; Frederik Wenkel; Luis Müller; Jama Hussein Mohamud; Ali Parviz; et al. (ICLR, 2024)

Real-World Molecular Out-Of-Distribution: Specification and Investigation. - Prudencio Tossou; Cas Wognum; Michael Craig; Hadrien Mary; Emmanuel Noutahi (J. Chem. Inf. Model., 2024)