| Sentry: Selective entropy optimization via committee consistency for unsupervised domain adaptation V Prabhu, S Khare, D Kartik, J Hoffman Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 102 | 2021 |
| Active domain adaptation via clustering uncertainty-weighted embeddings V Prabhu, A Chandrasekaran, K Saenko, J Hoffman Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 94 | 2021 |
| Do explanations make VQA models more predictable to a human? A Chandrasekaran, V Prabhu, D Yadav, P Chattopadhyay, D Parikh EMNLP 2018, 2018 | 90 | 2018 |
| Evaluating visual conversational agents via cooperative human-ai games P Chattopadhyay, D Yadav, V Prabhu, A Chandrasekaran, A Das, S Lee, ... Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 5 …, 2017 | 83 | 2017 |
| Few-shot learning for dermatological disease diagnosis V Prabhu, A Kannan, M Ravuri, M Chaplain, D Sontag, X Amatriain Machine Learning for Healthcare Conference, 532-552, 2019 | 71* | 2019 |
| It takes two to tango: Towards theory of AI's mind A Chandrasekaran, D Yadav, P Chattopadhyay, V Prabhu, D Parikh Chalearn Looking at People Workshop, CVPR, 2017, 2017 | 66 | 2017 |
| The promise of premise: Harnessing question premises in visual question answering A Mahendru, V Prabhu, A Mohapatra, D Batra, S Lee EMNLP 2017, 2017 | 36 | 2017 |
| Augco: augmentation consistency-guided self-training for source-free domain adaptive semantic segmentation V Prabhu, S Khare, D Kartik, J Hoffman Computer Vision in the Wild workshop, ECCV 2022, 2021 | 31* | 2021 |
| Udis: Unsupervised discovery of bias in deep visual recognition models A Krishnakumar, V Prabhu, S Sudhakar, J Hoffman British Machine Vision Conference (BMVC) 1 (2), 3, 2021 | 17 | 2021 |
| Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency V Prabhu, S Yenamandra, A Singh, J Hoffman NeurIPS 2022, 2022 | 8 | 2022 |
| Systems and methods for responding to healthcare inquiries A Kannan, M Ravuri, V Rodrigues, V Venkataraman, TSO Geoffrey, ... US Patent 10,847,265, 2020 | 8 | 2020 |
| Open set medical diagnosis V Prabhu, A Kannan, GJ Tso, N Katariya, M Chablani, D Sontag, ... ML4H workshop, NeurIPS 2019, 2019 | 7 | 2019 |
| Fabrik: An online collaborative neural network editor U Garg, V Prabhu, D Yadav, R Ramrakhya, H Agrawal, D Batra Workshop on AI Systems, SOSP 2019, 2018 | 5 | 2018 |
| Battle of the backbones: A large-scale comparison of pretrained models across computer vision tasks M Goldblum, H Souri, R Ni, M Shu, V Prabhu, G Somepalli, ... arXiv preprint arXiv:2310.19909, 2023 | 4 | 2023 |
| Can domain adaptation make object recognition work for everyone? V Prabhu, RR Selvaraju, J Hoffman, N Naik Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 3 | 2022 |
| Visdial-rl-pytorch N Modhe, V Prabhu, M Cogswell, S Kottur, A Das, S Lee, D Parikh, ... | 3 | 2018 |
| LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images V Prabhu, S Yenamandra, P Chattopadhyay, J Hoffman arXiv preprint arXiv:2305.19164, 2023 | 2 | 2023 |
| Mitigating bias in visual transformers via targeted alignment S Sudhakar, V Prabhu, A Krishnakumar, J Hoffman arXiv preprint arXiv:2302.04358, 2023 | 2 | 2023 |
| ICON: Reliably Benchmarking Predictive Inequity in Object Detection S Sudhakar, V Prabhu, O Russakovsky, J Hoffman arXiv preprint arXiv:2306.04482, 2023 | 1 | 2023 |
| Bridging the sim2real gap with care: Supervised detection adaptation with conditional alignment and reweighting V Prabhu, D Acuna, A Liao, R Mahmood, MT Law, J Hoffman, S Fidler, ... arXiv preprint arXiv:2302.04832, 2023 | 1 | 2023 |
Judy HoffmanAssistant Professor, Georgia TechVerified email at gatech.edu
