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Viraj Prabhu
Viraj Prabhu
Research Scientist, Salesforce AI Research
Verifisert e-postadresse på gatech.edu - Startside
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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
1672021
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
1652021
Do explanations make VQA models more predictable to a human?
A Chandrasekaran, V Prabhu, D Yadav, P Chattopadhyay, D Parikh
EMNLP 2018, 2018
1102018
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
942017
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
822017
xgen-mm (blip-3): A family of open large multimodal models
L Xue, M Shu, A Awadalla, J Wang, A Yan, S Purushwalkam, H Zhou, ...
arXiv preprint arXiv:2408.08872, 2024
702024
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, ...
Advances in Neural Information Processing Systems 36, 29343-29371, 2023
682023
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
682019
The promise of premise: Harnessing question premises in visual question answering
A Mahendru, V Prabhu, A Mohapatra, D Batra, S Lee
EMNLP 2017, 2017
492017
Lance: Stress-testing visual models by generating language-guided counterfactual images
V Prabhu, S Yenamandra, P Chattopadhyay, J Hoffman
Advances in Neural Information Processing Systems 36, 25165-25184, 2023
352023
UDIS: Unsupervised Discovery of Bias in Deep Visual Recognition Models.
A Krishnakumar, V Prabhu, S Sudhakar, J Hoffman
BMVC, 143, 2021
332021
Augco: augmentation consistency-guided self-training for source-free domain adaptive semantic segmentation
V Prabhu, S Khare, D Kartik, J Hoffman
arXiv preprint arXiv:2107.10140, 2021
24*2021
Facts: First amplify correlations and then slice to discover bias
S Yenamandra, P Ramesh, V Prabhu, J Hoffman
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
212023
Prototypical clustering networks for dermatological disease diagnosis
V Prabhu, A Kannan, M Ravuri, M Chablani, D Sontag, X Amatriain
arXiv preprint arXiv:1811.03066, 2018
172018
Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency
V Prabhu, S Yenamandra, A Singh, J Hoffman
NeurIPS 2022, 2022
162022
S4t: Source-free domain adaptation for semantic segmentation via self-supervised selective self-training
V Prabhu, S Khare, D Kartik, J Hoffman
arXiv preprint arXiv:2107.10140 2 (3), 6, 2021
162021
Systems and methods for responding to healthcare inquiries
A Kannan, M Ravuri, V Rodrigues, V Venkataraman, TSO Geoffrey, ...
US Patent 10,847,265, 2020
122020
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
102022
Open set medical diagnosis
V Prabhu, A Kannan, GJ Tso, N Katariya, M Chablani, D Sontag, ...
ML4H workshop, NeurIPS 2019, 2019
102019
Mitigating bias in visual transformers via targeted alignment
S Sudhakar, V Prabhu, A Krishnakumar, J Hoffman
arXiv preprint arXiv:2302.04358, 2023
92023
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Artikler 1–20