| Variational mixture-of-experts autoencoders for multi-modal deep generative models Y Shi, B Paige, P Torr Advances in neural information processing systems 32, 2019 | 321 | 2019 |
| Gradient matching for domain generalization Y Shi, J Seely, PHS Torr, N Siddharth, A Hannun, N Usunier, G Synnaeve arXiv preprint arXiv:2104.09937, 2021 | 314 | 2021 |
| Genie: Generative interactive environments J Bruce, MD Dennis, A Edwards, J Parker-Holder, Y Shi, E Hughes, M Lai, ... Forty-first International Conference on Machine Learning, 2024 | 115 | 2024 |
| Adversarial masking for self-supervised learning Y Shi, N Siddharth, P Torr, AR Kosiorek International Conference on Machine Learning, 20026-20040, 2022 | 99 | 2022 |
| Action anticipation with rbf kernelized feature mapping rnn Y Shi, B Fernando, R Hartley Proceedings of the European Conference on Computer Vision (ECCV), 301-317, 2018 | 98 | 2018 |
| Relating by contrasting: A data-efficient framework for multimodal DGMs Y Shi, B Paige, PHS Torr, N Siddharth Open Review, 2021 | 44* | 2021 |
| Tuning computer vision models with task rewards AS Pinto, A Kolesnikov, Y Shi, L Beyer, X Zhai International Conference on Machine Learning, 33229-33239, 2023 | 42 | 2023 |
| How robust are pre-trained models to distribution shift? Y Shi, I Daunhawer, JE Vogt, P Torr, A Sanyal ICML 2022: Workshop on Spurious Correlations, Invariance and Stability, 2022 | 35* | 2022 |
| Learning multimodal VAEs through mutual supervision T Joy, Y Shi, PHS Torr, T Rainforth, SM Schmon, N Siddharth arXiv preprint arXiv:2106.12570, 2021 | 30 | 2021 |
| Memory consolidation enables long-context video understanding I Balažević, Y Shi, P Papalampidi, R Chaabouni, S Koppula, OJ Hénaff arXiv preprint arXiv:2402.05861, 2024 | 11 | 2024 |
| Open-Endedness is Essential for Artificial Superhuman Intelligence E Hughes, M Dennis, J Parker-Holder, F Behbahani, A Mavalankar, Y Shi, ... arXiv preprint arXiv:2406.04268, 2024 | 10 | 2024 |
| Memory consolidation enables long-context video understanding I Balazevic, Y Shi, P Papalampidi, R Chaabouni, S Koppula, OJ Hénaff Forty-first International Conference on Machine Learning, 2024 | 10 | 2024 |
| Position: Open-Endedness is Essential for Artificial Superhuman Intelligence E Hughes, MD Dennis, J Parker-Holder, F Behbahani, A Mavalankar, ... Forty-first International Conference on Machine Learning, 0 | 3 | |
| Fine-tuning computer vision neural neworks using task rewards A Kolesnikov, X Zhai, AS Pinto, Y Shi, LK Beyer US Patent App. 18/438,317, 2024 | | 2024 |
Philip TorrProfessor, University of OxfordBestätigte E-Mail-Adresse bei eng.ox.ac.uk