| Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence A Chaudhry*, PK Dokania*, T Ajanthan*, PHS Torr In ECCV (2018), 2018 | 1416 | 2018 |
| Continual learning with tiny episodic memories A Chaudhry, M Rohrbach, M Elhoseiny, T Ajanthan, PK Dokania, ... In ICML 2019 Workshop on Multi-Task and Lifelong Reinforcement Learning, 2019 | 1064* | 2019 |
| GDumb: A Simple Approach that Questions Our Progress in Continual Learning A Prabhu, PHS Torr, PK Dokania In ECCV 2020, 2020 | 698 | 2020 |
| Calibrating Deep Neural Networks using Focal Loss J Mukhoti, V Kulharia, A Sanyal, S Golodetz, PHS Torr, PK Dokania In NeurIPS 2020, 2020 | 556 | 2020 |
| Learning-based approach for online lane change intention prediction P Kumar, M Perrollaz, S Lefevre, C Laugier 2013 IEEE Intelligent Vehicles Symposium (IV), 797-802, 2013 | 512 | 2013 |
| Multi-Agent Diverse Generative Adversarial Networks A Ghosh, V Kulharia, V Namboodiri, PHS Torr, PK Dokania In CVPR (2018), 2017 | 418 | 2017 |
| Using hindsight to anchor past knowledge in continual learning A Chaudhry, A Gordo, PK Dokania, P Torr, D Lopez-Paz In AAAI 2021, 2021 | 267 | 2021 |
| Discovering Class-Specific Pixels for Weakly-Supervised Semantic Segmentation A Chaudhry, PK Dokania, PHS Torr British Machine Vision Conference (BMVC 2017), 2017 | 165 | 2017 |
| Interactive sketch & fill: Multiclass sketch-to-image translation A Ghosh, R Zhang, PK Dokania, O Wang, AA Efros, PHS Torr, ... In ICCV (2019), 1171-1180, 2019 | 163 | 2019 |
| Continual Learning in Low-rank Orthogonal Subspaces A Chaudhry, N Khan, PK Dokania, PHS Torr In NeurIPS 2020, 2020 | 143 | 2020 |
| Progressive skeletonization: Trimming more fat from a network at initialization P de Jorge, A Sanyal, HS Behl, PHS Torr, G Rogez, PK Dokania In ICLR 2021, 2021 | 117 | 2021 |
| Graph Inductive Biases in Transformers without Message Passing L Ma, C Lin, D Lim, A Romero-Soriano, PK Dokania, M Coates, P Torr, ... In ICML 2023, 2023 | 114 | 2023 |
| RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness F Pinto, H Yang, SN Lim, PHS Torr, PK Dokania Neural Information Processing Systems (NeurIPS) 2022, 2022 | 103* | 2022 |
| A novel bacterial foraging technique for edge detection OP Verma, M Hanmandlu, P Kumar, S Chhabra, A Jindal Pattern recognition letters 32 (8), 1187-1196, 2011 | 102 | 2011 |
| High dynamic range optimal fuzzy color image enhancement using artificial ant colony system OP Verma, P Kumar, M Hanmandlu, S Chhabra Applied Soft Computing 12 (1), 394-404, 2012 | 93 | 2012 |
| Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs A Osokin, JB Alayrac, I Lukasewitz, PK Dokania, S Lacoste-Julien In ICML (2016), 2016 | 89 | 2016 |
| How benign is benign overfitting? A Sanyal, PK Dokania, V Kanade, PHS Torr In ICLR 2021, 2021 | 73 | 2021 |
| Computationally Budgeted Continual Learning: What Does Matter? A Prabhu, HAAK Hammoud, P Dokania, PHS Torr, SN Lim, B Ghanem, ... In CVPR 2023, 2023 | 71 | 2023 |
| An Impartial Take to the CNN vs Transformer Robustness Contest F Pinto, PHS Torr, PK Dokania In The European Conference on Computer Vision (ECCV) 2022, 2022 | 70* | 2022 |
| Make Some Noise: Reliable and Efficient Single-Step Adversarial Training P de Jorge, A Bibi, R Volpi, A Sanyal, PHS Torr, G Rogez, PK Dokania Neural Information Processing Systems (NeurIPS) 2022, 2022 | 63* | 2022 |
Philip TorrProfessor, University of Oxfordeng.ox.ac.uk의 이메일 확인됨
