Dominic Masters

According to our database, Dominic Masters authored at least 9 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters

CoRR, 2023

PopSparse: Accelerated block sparse matrix multiplication on IPU.

Zhiyi Li, Douglas Orr, Valeriu Ohan, Godfrey Da Costa, Tom Murray, Adam Sanders, Deniz Beker, Dominic Masters

CoRR, 2023

GPS++: Reviving the Art of Message Passing for Molecular Property Prediction.

Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W. Fitzgibbon, Shenyang Huang, Ladislav Rampásek, Dominique Beaini

CoRR, 2023

Generating QM1B with PySCF_IPU.

Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction.

Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Ladislav Rampásek, Dominique Beaini

CoRR, 2022

8-bit Numerical Formats for Deep Neural Networks.

Badreddine Noune, Philip Jones, Daniel Justus, Dominic Masters, Carlo Luschi

CoRR, 2022

2021

Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training.

Dominic Masters, Antoine Labatie, Zach Eaton-Rosen, Carlo Luschi

CoRR, 2021

Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence.

Antoine Labatie, Dominic Masters, Zach Eaton-Rosen, Carlo Luschi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2018

Revisiting Small Batch Training for Deep Neural Networks.

Dominic Masters, Carlo Luschi

CoRR, 2018