| GDumb: A Simple Approach that Questions Our Progress in Continual Learning A Prabhu, PHS Torr, PK Dokania Proceedings of the European Conference on Computer Vision (ECCV) 2020, 2020 | 696 | 2020 |
| Towards sub-word level compositions for sentiment analysis of hindi-english code mixed text A Joshi, A Prabhu, M Shrivastava, V Varma Proceedings of COLING 2016, the 26th International Conference on …, 2016 | 220* | 2016 |
| Inverse scaling: When bigger isn't better IR McKenzie, A Lyzhov, M Pieler, A Parrish, A Mueller, A Prabhu, ... Transactions of Machine Learning Research (TMLR), 2023 | 151* | 2023 |
| Simple unsupervised multi-object tracking S Karthik, A Prabhu, V Gandhi arXiv preprint arXiv:2006.02609, 2020 | 103 | 2020 |
| Deep expander networks: Efficient deep networks from graph theory A Prabhu, G Varma, A Namboodiri Proceedings of the European Conference on Computer Vision (ECCV), 20-35, 2018 | 91 | 2018 |
| Sampling Bias in Deep Active Classification: An Empirical Study A Prabhu, C Dognin, M Singh 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP …, 2019 | 77 | 2019 |
| Computationally budgeted continual learning: What does matter? A Prabhu, HA Al Kader Hammoud, PK Dokania, PHS Torr, SN Lim, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 71 | 2023 |
| Real-time evaluation in online continual learning: A new hope Y Ghunaim, A Bibi, K Alhamoud, M Alfarra, HA Al Kader Hammoud, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 70* | 2023 |
| Towards adversarial evaluations for inexact machine unlearning S Goel, A Prabhu, A Sanyal, SN Lim, P Torr, P Kumaraguru arXiv preprint arXiv:2201.06640, 2022 | 67* | 2022 |
| Towards deep learning in hindi ner: An approach to tackle the labelled data scarcity V Athavale, S Bharadwaj, M Pamecha, A Prabhu, M Shrivastava arXiv preprint arXiv:1610.09756, 2016 | 63 | 2016 |
| No" zero-shot" without exponential data: Pretraining concept frequency determines multimodal model performance V Udandarao, A Prabhu, A Ghosh, Y Sharma, P Torr, A Bibi, S Albanie, ... The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 46 | 2024 |
| Online continual learning without the storage constraint A Prabhu, Z Cai, P Dokania, P Torr, V Koltun, O Sener arXiv preprint arXiv:2305.09253, 2023 | 37 | 2023 |
| Corrective machine unlearning S Goel, A Prabhu, P Torr, P Kumaraguru, A Sanyal arXiv preprint arXiv:2402.14015, 2024 | 29 | 2024 |
| No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks S Karthik, A Prabhu, PK Dokania, V Gandhi International Conference on Learning Representations (ICLR), 2021, 2021 | 25 | 2021 |
| Humanity's Last Exam L Phan, A Gatti, Z Han, N Li, J Hu, H Zhang, CBC Zhang, M Shaaban, ... arXiv preprint arXiv:2501.14249, 2025 | 24 | 2025 |
| Hybrid binary networks: optimizing for accuracy, efficiency and memory A Prabhu, V Batchu, R Gajawada, SA Munagala, A Namboodiri 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 821-829, 2018 | 19 | 2018 |
| Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? HA Al Kader Hammoud, A Prabhu, SN Lim, PHS Torr, A Bibi, B Ghanem Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 18* | 2023 |
| Open problems in machine unlearning for ai safety F Barez, T Fu, A Prabhu, S Casper, A Sanyal, A Bibi, A O'Gara, R Kirk, ... arXiv preprint arXiv:2501.04952, 2025 | 11 | 2025 |
| From categories to classifier: Name-only continual learning by exploring the web A Prabhu, HAAK Hammoud, SN Lim, B Ghanem, PHS Torr, A Bibi Third Conference on Lifelong Learning Agents (CoLLAs) - Oral, 2023 | 10 | 2023 |
| Efficient Lifelong Model Evaluation in an Era of Rapid Progress A Prabhu, V Udandarao, P Torr, M Bethge, A Bibi, S Albanie The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 8* | 2024 |
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
