| Alpha MAML: Adaptive Model-Agnostic Meta-Learning HS Behl, AG Baydin, PHS Torr ICML 2019 Workshops, 2019 | 47 | 2019 |
| STEER: Simple Temporal Regularization For Neural ODEs A Ghosh, HS Behl, PHS Torr, V Namboodiri NeurIPS 2020, 2020 | 27 | 2020 |
| Progressive skeletonization: Trimming more fat from a network at initialization P de Jorge, A Sanyal, HS Behl, PHS Torr, G Rogez, PK Dokania ICLR 2021, 2020 | 20 | 2020 |
| Incremental Tube Construction for Human Action Detection HS Behl, M Sapienza, G Singh, S Saha, F Cuzzolin, PHS Torr BMVC 2018, 2017 | 20 | 2017 |
| Meta learning deep visual words for fast video object segmentation HS Behl, M Najafi, A Arnab, PHS Torr IROS 2020, 2018 | 15 | 2018 |
| Scaling the Convex Barrier with Active Sets A De Palma, HS Behl, R Bunel, PHS Torr, MP Kumar ICLR 2021, 2021 | 14 | 2021 |
| AutoSimulate: (Quickly) Learning Synthetic Data Generation HS Behl, AG Baydin, R Gal, PHS Torr, V Vineet ECCV 2020, 2020 | 12 | 2020 |
| Scaling the convex barrier with sparse dual algorithms A De Palma, HS Behl, R Bunel, PHS Torr, MP Kumar arXiv preprint arXiv:2101.05844, 2021 | 3 | 2021 |
| Overcoming the Convex Barrier for Simplex Inputs HS Behl, MP Kumar, P Torr, K Dvijotham Advances in Neural Information Processing Systems 34, 2021 | 1 | 2021 |
| Automated and verified deep learning HS Behl University of Oxford, 2021 | | 2021 |
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
