| Revisiting small batch training for deep neural networks D Masters, C Luschi arXiv preprint arXiv:1804.07612, 2018 | 1048 | 2018 |
| Geometric comparison of aerofoil shape parameterization methods DA Masters, NJ Taylor, TCS Rendall, CB Allen, DJ Poole AIAA journal 55 (5), 1575-1589, 2017 | 188 | 2017 |
| Review of aerofoil parameterisation methods for aerodynamic shape optimisation DA Masters, NJ Taylor, T Rendall, CB Allen, DJ Poole 53rd AIAA aerospace sciences meeting, 0761, 2015 | 70 | 2015 |
| Impact of shape parameterisation on aerodynamic optimisation of benchmark problem DA Masters, DJ Poole, NJ Taylor, T Rendall, CB Allen 54th AIAA Aerospace Sciences Meeting, 1544, 2016 | 40 | 2016 |
| Influence of shape parameterization on a benchmark aerodynamic optimization problem DA Masters, DJ Poole, NJ Taylor, TCS Rendall, CB Allen Journal of Aircraft 54 (6), 2242-2256, 2017 | 39 | 2017 |
| Multilevel subdivision parameterization scheme for aerodynamic shape optimization DA Masters, NJ Taylor, TCS Rendall, CB Allen AIAA Journal 55 (10), 3288-3303, 2017 | 33 | 2017 |
| 8-bit numerical formats for deep neural networks B Noune, P Jones, D Justus, D Masters, C Luschi arXiv preprint arXiv:2206.02915, 2022 | 30 | 2022 |
| Proxy-normalizing activations to match batch normalization while removing batch dependence A Labatie, D Masters, Z Eaton-Rosen, C Luschi Advances in Neural Information Processing Systems 34, 16990-17006, 2021 | 20 | 2021 |
| Gps++: An optimised hybrid mpnn/transformer for molecular property prediction D Masters, J Dean, K Klaser, Z Li, S Maddrell-Mander, A Sanders, H Helal, ... arXiv preprint arXiv:2212.02229, 2022 | 18 | 2022 |
| Progressive subdivision curves for aerodynamic shape optimisation DA Masters, NJ Taylor, T Rendall, CB Allen 54th AIAA Aerospace Sciences Meeting, 0559, 2016 | 18 | 2016 |
| A locally adaptive subdivision parameterisation scheme for aerodynamic shape optimisation DA Masters, NJ Taylor, T Rendall, CB Allen 34th AIAA Applied Aerodynamics Conference, 3866, 2016 | 18 | 2016 |
| Towards foundational models for molecular learning on large-scale multi-task datasets D Beaini, S Huang, JA Cunha, G Moisescu-Pareja, O Dymov, ... arXiv preprint arXiv:2310.04292, 2023 | 12 | 2023 |
| Validation of the aerodynamic loading on basic flying disc geometries derived from CFD simulations JR Potts, D Masters Procedia Engineering 112, 400-405, 2015 | 11 | 2015 |
| Making EfficientNet more efficient: Exploring batch-independent normalization, group convolutions and reduced resolution training D Masters, A Labatie, Z Eaton-Rosen, C Luschi arXiv preprint arXiv:2106.03640, 2021 | 7 | 2021 |
| Three-dimensional subdivision parameterisation for aerodynamic shape optimisation DA Masters, NJ Taylor, T Rendall, CB Allen 55th AIAA Aerospace Sciences Meeting, 0036, 2017 | 6 | 2017 |
| Generating QM1B with PySCF A Mathiasen, H Helal, K Klaser, P Balanca, J Dean, C Luschi, D Beaini, ... Advances in Neural Information Processing Systems 36, 55036-55050, 2023 | 4 | 2023 |
| Gps++: Reviving the art of message passing for molecular property prediction D Masters, J Dean, K Klaser, Z Li, S Maddrell-Mander, A Sanders, H Helal, ... arXiv preprint arXiv:2302.02947, 2023 | 4 | 2023 |
| Repurposing density functional theory to suit deep learning A Mathiasen, H Helal, P Balanca, K Klaeser, J Dean, C Luschi, D Beaini, ... 1st Workshop on the Synergy of Scientific and Machine Learning Modeling …, 2023 | 1 | 2023 |
| Overflow Event Counter A Alexander, D Masters US Patent App. 18/483,699, 2024 | | 2024 |
| Processing Device for Intermediate Value Scaling A Alexander, S Knowles, S Felix, C Luschi, B Noune, M Gore, G Da Costa, ... US Patent App. 18/175,050, 2023 | | 2023 |
