| Meta-learning probabilistic inference for prediction J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner arXiv preprint arXiv:1805.09921, 2018 | 266 | 2018 |
| Fast and flexible multi-task classification using conditional neural adaptive processes J Requeima, J Gordon, J Bronskill, S Nowozin, RE Turner Advances in Neural Information Processing Systems 32, 2019 | 216 | 2019 |
| Infer .NET 0.3, 2018. Microsoft Research Cambridge T Minka, J Winn, J Guiver, Y Zaykov, D Fabian, J Bronskill | 191* | |
| Tasknorm: Rethinking batch normalization for meta-learning J Bronskill, J Gordon, J Requeima, S Nowozin, R Turner International Conference on Machine Learning, 1153-1164, 2020 | 96 | 2020 |
| Mixed but indistinguishable raster and vector image data types AR Smith, J Bradstreet, JE Fay, A Sehgal, TA Joshi, JF Bronskill, ... US Patent 7,148,907, 2006 | 63 | 2006 |
| System and method for drawing and painting with bitmap brushes J Bronskill US Patent 6,201,549, 2001 | 58 | 2001 |
| Fs-mol: A few-shot learning dataset of molecules M Stanley, JF Bronskill, K Maziarz, H Misztela, J Lanini, M Segler, ... Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 50 | 2021 |
| Multidimensional shape description and recognition using mathematical morphology JF Bronskill, AN Venetsanopoulos Journal of Intelligent and Robotic systems 1, 117-143, 1988 | 41 | 1988 |
| Orbit: A real-world few-shot dataset for teachable object recognition D Massiceti, L Zintgraf, J Bronskill, L Theodorou, MT Harris, E Cutrell, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 40 | 2021 |
| Apparatus and method for transforming a digitized signal of an image I Jaffray, JF Bronskill US Patent 5,063,448, 1991 | 39 | 1991 |
| Apparatus and method for transforming a digitized signal of an image to incorporate an airbrush effect I Jaffray, JF Bronskill US Patent 5,245,432, 1993 | 38 | 1993 |
| Personalized predictive models J Edelen, J Li, JF Bronskill, JP Guiver, K Dastgir, S Rajmohan, ... US Patent 10,504,029, 2019 | 34 | 2019 |
| Rich data-bound application J Gossman, K Cooper, T Peters, J Bronskill, DR Motter, A Gasperini, ... US Patent App. 11/080,531, 2006 | 29 | 2006 |
| Memory efficient meta-learning with large images J Bronskill, D Massiceti, M Patacchiola, K Hofmann, S Nowozin, R Turner Advances in Neural Information Processing Systems 34, 24327-24339, 2021 | 21 | 2021 |
| System and method for drawing and painting with warped bitmap brushes J Bronskill, M Gangnet US Patent 7,158,138, 2007 | 18 | 2007 |
| A knowledge-based approach to the detection, tracking and classification of target formations in infrared image sequences JF Bronskill, JSA Hepburn, WK Au 1989 IEEE Computer Society Conference on Computer Vision and Pattern …, 1989 | 16 | 1989 |
| Fit: Parameter efficient few-shot transfer learning for personalized and federated image classification A Shysheya, J Bronskill, M Patacchiola, S Nowozin, RE Turner arXiv preprint arXiv:2206.08671, 2022 | 12 | 2022 |
| Versa: Versatile and efficient few-shot learning J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner Third workshop on Bayesian Deep Learning, 2018 | 12 | 2018 |
| The pecstrum JF Bronskill, AN Venetsanopoulos Proceedings of the 3rd ASSP Workshop on Spectral Estimation and Modeling; Boston, 1986 | 9 | 1986 |
| Contextual squeeze-and-excitation for efficient few-shot image classification M Patacchiola, J Bronskill, A Shysheya, K Hofmann, S Nowozin, R Turner Advances in Neural Information Processing Systems 35, 36680-36692, 2022 | 8 | 2022 |
Richard E TurnerProfessor, University of CambridgeVerified email at cam.ac.uk
