| Meta-learning with differentiable convex optimization K Lee, S Maji, A Ravichandran, S Soatto Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 1404 | 2019 |
| Histograms of oriented optical flow and binet-cauchy kernels on nonlinear dynamical systems for the recognition of human actions R Chaudhry, A Ravichandran, G Hager, R Vidal 2009 IEEE conference on computer vision and pattern recognition, 1932-1939, 2009 | 895 | 2009 |
| A baseline for few-shot image classification GS Dhillon, P Chaudhari, A Ravichandran, S Soatto arXiv preprint arXiv:1909.02729, 2019 | 640 | 2019 |
| A closed form solution to robust subspace estimation and clustering P Favaro, R Vidal, A Ravichandran CVPR 2011, 1801-1807, 2011 | 373 | 2011 |
| Task2vec: Task embedding for meta-learning A Achille, M Lam, R Tewari, A Ravichandran, S Maji, CC Fowlkes, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 318 | 2019 |
| Few-shot learning with embedded class models and shot-free meta training A Ravichandran, R Bhotika, S Soatto Proceedings of the IEEE/CVF international conference on computer vision, 331-339, 2019 | 203 | 2019 |
| View-invariant dynamic texture recognition using a bag of dynamical systems A Ravichandran, R Chaudhry, R Vidal 2009 IEEE conference on computer vision and pattern recognition, 1651-1657, 2009 | 153 | 2009 |
| Optical flow estimation & segmentation of multiple moving dynamic textures R Vidal, A Ravichandran Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer …, 2005 | 140 | 2005 |
| Rethinking the hyperparameters for fine-tuning H Li, P Chaudhari, H Yang, M Lam, A Ravichandran, R Bhotika, S Soatto arXiv preprint arXiv:2002.11770, 2020 | 134 | 2020 |
| Categorizing Dynamic Textures using a Bag of Dynamical Systems A Ravichandran, R Chaudhry, R Vidal IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012 | 132 | 2012 |
| Mixed-privacy forgetting in deep networks A Golatkar, A Achille, A Ravichandran, M Polito, S Soatto Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 116 | 2021 |
| Exponential moving average normalization for self-supervised and semi-supervised learning Z Cai, A Ravichandran, S Maji, C Fowlkes, Z Tu, S Soatto Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 99 | 2021 |
| Winclip: Zero-/few-shot anomaly classification and segmentation J Jeong, Y Zou, T Kim, D Zhang, A Ravichandran, O Dabeer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 77 | 2023 |
| Task adaptive parameter sharing for multi-task learning M Wallingford, H Li, A Achille, A Ravichandran, C Fowlkes, R Bhotika, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 60 | 2022 |
| Video Registration Using Dynamic Textures A Ravichandran, R Vidal European Conference on Computer Vision, 514-526, 2008 | 57 | 2008 |
| Class-incremental learning with strong pre-trained models TY Wu, G Swaminathan, Z Li, A Ravichandran, N Vasconcelos, R Bhotika, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 54 | 2022 |
| Cluster-trained machine learning for image processing MF Tappen, AA Ravichandran, H Boyraz, B Liu US Patent 9,704,054, 2017 | 49 | 2017 |
| X-detr: A versatile architecture for instance-wise vision-language tasks Z Cai, G Kwon, A Ravichandran, E Bas, Z Tu, R Bhotika, S Soatto European Conference on Computer Vision, 290-308, 2022 | 44 | 2022 |
| Group action induced distances for averaging and clustering Linear Dynamical Systems with applications to the analysis of dynamic scenes B Afsari, R Chaudhry, A Ravichandran, R Vidal Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on …, 2012 | 44 | 2012 |
| Semi-supervised vision transformers at scale Z Cai, A Ravichandran, P Favaro, M Wang, D Modolo, R Bhotika, Z Tu, ... Advances in Neural Information Processing Systems 35, 25697-25710, 2022 | 43 | 2022 |
Stefano SoattoProfessor of Computer Science, UCLA; Vice President, AWS AI在 ucla.edu 的电子邮件经过验证
