| Dinov2: Learning robust visual features without supervision M Oquab, T Darcet, T Moutakanni, H Vo, M Szafraniec, V Khalidov, ... arXiv preprint arXiv:2304.07193, 2023 | 1146 | 2023 |
| The deepfake detection challenge (dfdc) dataset B Dolhansky, J Bitton, B Pflaum, J Lu, R Howes, M Wang, CC Ferrer arXiv preprint arXiv:2006.07397, 2020 | 732 | 2020 |
| The deepfake detection challenge (dfdc) preview dataset B Dolhansky, R Howes, B Pflaum, N Baram, CC Ferrer arXiv preprint arXiv:1910.08854, 2019 | 540 | 2019 |
| Energetically Consistent Invertible Elasticity A Stomakhin, R Howes, C Schroeder, JM Teran Eurographics/ACM SIGGRAPH Symposium on Computer Animation, 25-32, 2012 | 135 | 2012 |
| Scaling autoregressive multi-modal models: Pretraining and instruction tuning L Yu, B Shi, R Pasunuru, B Muller, O Golovneva, T Wang, A Babu, B Tang, ... arXiv preprint arXiv:2309.02591 2 (3), 2023 | 79 | 2023 |
| Demystifying clip data H Xu, S Xie, XE Tan, PY Huang, R Howes, V Sharma, SW Li, G Ghosh, ... arXiv preprint arXiv:2309.16671, 2023 | 67 | 2023 |
| SeamlessM4T-Massively Multilingual & Multimodal Machine Translation L Barrault, YA Chung, MC Meglioli, D Dale, N Dong, PA Duquenne, ... arXiv preprint arXiv:2308.11596, 2023 | 56 | 2023 |
| Dynamical structure functions for the reverse engineering of LTI networks J Gonçalves, R Howes, S Warnick 2007 46th IEEE Conference on Decision and Control, 1516-1522, 2007 | 42 | 2007 |
| The llama 3 herd of models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 37 | 2024 |
| The deepfake detection challenge (dfdc) dataset. arXiv 2020 B Dolhansky, J Bitton, B Pflaum, J Lu, R Howes, M Wang, CC Ferrer arXiv preprint arXiv:2006.07397, 2006 | 32 | 2006 |
| Cit: Curation in training for effective vision-language data H Xu, S Xie, PY Huang, L Yu, R Howes, G Ghosh, L Zettlemoyer, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 20 | 2023 |
| Dynamical structure analysis of sparsity and minimality heuristics for reconstruction of biochemical networks R Howes, L Eccleston, J Gonçalves, GB Stan, S Warnick 2008 47th IEEE Conference on Decision and Control, 173-178, 2008 | 19 | 2008 |
| The deepfake detection challenge (dfdc) preview dataset. arXiv 2019 B Dolhansky, R Howes, B Pflaum, N Baram, CC Ferrer arXiv preprint arXiv:1910.08854, 0 | 17 | |
| A second order virtual node algorithm for Navier–Stokes flow problems with interfacial forces and discontinuous material properties C Schroeder, A Stomakhin, R Howes, JM Teran Journal of Computational Physics 265, 221-245, 2014 | 13 | 2014 |
| The deepfake detection challenge (dfdc) dataset (2020) B Dolhansky, J Bitton, B Pflaum, J Lu, R Howes, M Wang, CC Ferrer arXiv preprint arXiv:2006.07397, 2006 | 12 | 2006 |
| Dinov2: Learning robust visual features without supervision (2023) M Oquab, T Darcet, T Moutakanni, H Vo, M Szafraniec, V Khalidov, ... arXiv preprint arXiv:2304.07193 1, 0 | 12 | |
| A comparison of network reconstruction methods for chemical reaction networks C Ward, E Yeung, T Brown, B Durtschi, S Weyerman, R Howes, ... Third International Conference on Foundations of Systems Biology in …, 2009 | 11 | 2009 |
| The DeepFake detection challenge dataset.(2020) B Dolhansky, J Bitton, B Pflaum, J Lu, R Howes, M Wang, CC Ferrer ArXiv: abs, 2006 | 11 | 2006 |
| Adversarial Evaluation of Multimodal Models under Realistic Gray Box Assumption I Evtimov, R Howes, B Dolhansky, H Firooz, CC Ferrer arXiv preprint arXiv:2011.12902, 2020 | 9 | 2020 |
| Automated generation of failure modes and effects analyses from aadl architectural and error models M Hecht, A Lam, R Howes, C Vogl, S Lake Presented at the 22nd Systems and Software Technology Conference (SSTC) 26, 29, 2010 | 8 | 2010 |
Guy-Bart StanProfessor of BioSystems Engineering and Control, RAEng Chair, Bioengineering, Imperial College在 imperial.ac.uk 的电子邮件经过验证
Guy-Bart StanProfessor of BioSystems Engineering and Control, RAEng Chair, Bioengineering, Imperial College在 imperial.ac.uk 的电子邮件经过验证