Studying the Potential of Graphcore® IPUs for Applications in Particle Physics. - Samuel Maddrell-Mander; Lakshan Ram Madhan Mohan; Alexander Marshall; Daniel O'Hanlon; Konstantinos Petridis; Jonas Rademacker; Victoria Rege; Alexander Titterton (Comput. Softw. Big Sci., 2021)

GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction. - Dominic Masters; Josef Dean; Kerstin Klaser 001; Zhiyi Li; Sam Maddrell-Mander; Adam Sanders; Hatem Helal; Deniz Beker; Ladislav Rampásek; Dominique Beaini (CoRR, 2022)

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)

GPS++: Reviving the Art of Message Passing for Molecular Property Prediction. - Dominic Masters; Josef Dean; Kerstin Kläser 001; Zhiyi Li; Samuel Maddrell-Mander; Adam Sanders; Hatem Helal; Deniz Beker; Andrew W. Fitzgibbon; Shenyang Huang; Ladislav Rampásek; Dominique Beaini (Trans. Mach. Learn. Res., 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)

MiniMol: A Parameter-Efficient Foundation Model for Molecular Learning. - Kerstin Kläser 001; Blazej Banaszewski; Samuel Maddrell-Mander; Callum McLean; Luis Müller; Ali Parviz; Shenyang Huang; Andrew W. Fitzgibbon (CoRR, 2024)