Dominic Masters

15 papers A* 3Journal 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Probabilistic weather forecasting with machine learning. Nat. Ilan Price, Alvaro Sanchez-Gonzalez, Ferran Alet, Tom R. Andersson, Andrew El-Kadi, Dominic Masters, Timo Ewalds, Jacklynn Stott, Shakir Mohamed, Peter W. Battaglia, Rémi R. Lam, Matthew Willson
2025	J	`jnl`	Skillful joint probabilistic weather forecasting from marginals. CoRR Ferran Alet, Ilan Price, Andrew El-Kadi, Dominic Masters, Stratis Markou, Tom R. Andersson, Jacklynn Stott, Rémi Lam, Matthew Willson, Alvaro Sanchez-Gonzalez, Peter W. Battaglia
2024	A*	`conf`	Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. ICLR 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, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
2023	J	`jnl`	GPS++: Reviving the Art of Message Passing for Molecular Property Prediction. CoRR 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
2023	J	`jnl`	GPS++: Reviving the Art of Message Passing for Molecular Property Prediction. Trans. Mach. Learn. Res. Dominic Masters, Josef Dean, Kerstin Kläser, Zhiyi Li, Samuel Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W. Fitzgibbon, Shenyang Huang, Ladislav Rampásek, Dominique Beaini
2023	A*	`conf`	Generating QM1B with PySCF NeurIPS Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters
2023	J	`jnl`	Generating QM1B with PySCF CoRR Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters
2023	J	`jnl`	PopSparse: Accelerated block sparse matrix multiplication on IPU. CoRR Zhiyi Li, Douglas Orr, Valeriu Ohan, Godfrey Da Costa, Tom Murray, Adam Sanders, Deniz Beker, Dominic Masters
2023	J	`jnl`	Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. CoRR 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
2022	J	`jnl`	8-bit Numerical Formats for Deep Neural Networks. CoRR Badreddine Noune, Philip Jones, Daniel Justus, Dominic Masters, Carlo Luschi
2022	J	`jnl`	GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction. CoRR Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Ladislav Rampásek, Dominique Beaini
2021	J	`jnl`	Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training. CoRR Dominic Masters, Antoine Labatie, Zach Eaton-Rosen, Carlo Luschi
2021	A*	`conf`	Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence. NeurIPS Antoine Labatie, Dominic Masters, Zach Eaton-Rosen, Carlo Luschi
2021	J	`jnl`	Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence. CoRR Antoine Labatie, Dominic Masters, Zach Eaton-Rosen, Carlo Luschi
2018	J	`jnl`	Revisiting Small Batch Training for Deep Neural Networks. CoRR Dominic Masters, Carlo Luschi