Pritish Sahu is an in Ph.D. program at the computer science department of Rutgers, the State University of New Jersey. He joined Seqam Lab headed by Dr. Pavlovic in Spring 2018. He obtained his M.S. degree from the Computer Science Department at Rutgers University and B.Tech from National Institute of Technology, Rourkela, India.
His research interest are in Machine Learning and Computer Vision. He is currently working on problems pertaining to transfer learning and the disentanglement of latent features deep learning using deep learning. You can follow my research on my personal websiteLink
2025
- K. Baisoti, P. Sahu, T. Q. Liu, Z. Xu, H. Wang, and V. Pavlovic, “GenVP: Generating Visual Puzzles With Contrastive Hierarchical VAEs,” in 13h International Conference on Learning Representations, ICLR 2025, 2025.
[BibTeX] [Download PDF]@inproceedings{basioti25iclr, author = {Kalliopi Baisoti and Pritish Sahu and Tony Qingze Liu and Zihao Xu and Hao Wang and Vladimir Pavlovic}, title = {{GenVP}: Generating Visual Puzzles With Contrastive Hierarchical {VAE}s}, booktitle = {13h International Conference on Learning Representations, {ICLR} 2025}, month = {April}, year = {2025}, url = {https://arxiv.org/pdf/2503.23598} }
2024
- K. Basioti, P. Sahu, T. Q. Liu, Z. Xu, H. Wang, and V. Pavlovic, “Generative Visual Puzzles with Global-Local Masked Contrastive HVAEs,” , 2024.
[BibTeX]@article{basioti24neurips, author = {Kalliopi Basioti and Pritish Sahu and Tony Qingze Liu and Zihao Xu and Hao Wang and Vladimir Pavlovic}, title = {Generative Visual Puzzles with Global-Local Masked Contrastive {HVAE}s}, journal = {}, year = {2024}, note = {Under review} }
2023
- P. Sahu, K. Basioti, and A. M. V. Pavlovic, “Spatially Attentive Transformers for Abstract Visual Reasoning,” IEEE Transactions on Neural Networks and Learning Systems, 2023.
[BibTeX]@article{sahu23tnnls, author = {Pritish Sahu and Kalliopi Basioti and Alen Mrdovi\'c Vladimir Pavlovic}, title = {Spatially Attentive Transformers for Abstract Visual Reasoning}, journal = {{IEEE} Transactions on Neural Networks and Learning Systems}, year = {2023}, note = {Under review} }
2022
- P. Sahu, K. Basioti, and V. Pavlovic, “SAViR-T: Spatially Attentive Visual Reasoning with Transformers,” in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2022, 2022.
[BibTeX] [Download PDF]@inproceedings{sahu22ecml, author = {Pritish Sahu and Kalliopi Basioti and Vladimir Pavlovic}, title = {SAViR-T: Spatially Attentive Visual Reasoning with Transformers}, booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, {ECML-PKDD} 2022}, year = {2022}, url = {https://arxiv.org/abs/2206.09265}, timestamp = {Mon, 04 Oct 2021 17:22:25 +0200}, biburl = {https://dblp.org/rec/journals/corr/abs-2109-13156.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - P. Sahu, K. Basioti, and V. Pavlovic, “DAReN: A Collaborative Approach Towards Reasoning And Disentangling,” in 26th International Conference on Pattern Recognition, ICPR 2022, 2022.
[BibTeX] [Download PDF]@inproceedings{sahu22icpr, author = {Pritish Sahu and Kalliopi Basioti and Vladimir Pavlovic}, title = {DAReN: {A} Collaborative Approach Towards Reasoning And Disentangling}, booktitle = {26th International Conference on Pattern Recognition, {ICPR} 2022}, year = {2022}, url = {https://arxiv.org/abs/2109.13156}, note = {2022 Piero Zamperoni Best Student Paper Award}, biburl = {https://dblp.org/rec/journals/corr/abs-2109-13156.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - P. Sahu, K. Basioti, and V. Pavlovic, “SAViR-T: Spatially Attentive Visual Reasoning with Transformers,” CoRR, vol. abs/2206.09265, 2022. doi:10.48550/arXiv.2206.09265
[BibTeX] [Download PDF]@article{sahu22abs-2206-09265, author = {Pritish Sahu and Kalliopi Basioti and Vladimir Pavlovic}, title = {SAViR-T: Spatially Attentive Visual Reasoning with Transformers}, journal = {CoRR}, volume = {abs/2206.09265}, year = {2022}, url = {https://doi.org/10.48550/arXiv.2206.09265}, doi = {10.48550/arXiv.2206.09265}, eprinttype = {arXiv}, eprint = {2206.09265}, timestamp = {Tue, 11 Oct 2022 14:59:07 +0200}, biburl = {https://dblp.org/rec/journals/corr/abs-2206-09265.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2021
- P. Sahu and V. Pavlovic, “DAReN: A Collaborative Approach Towards Reasoning And Disentangling,” CoRR, vol. abs/2109.13156, 2021.
[BibTeX] [Download PDF]@article{sahu21arx, author = {Pritish Sahu and Vladimir Pavlovic}, title = {DAReN: {A} Collaborative Approach Towards Reasoning And Disentangling}, journal = {CoRR}, volume = {abs/2109.13156}, year = {2021}, url = {https://arxiv.org/abs/2109.13156}, eprinttype = {arXiv}, eprint = {2109.13156}, timestamp = {Mon, 04 Oct 2021 17:22:25 +0200}, biburl = {https://dblp.org/rec/journals/corr/abs-2109-13156.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2020
- B. Gholami, P. Sahu, O. Rudovic, K. Bousmalis, and V. Pavlovic, “Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach,” IEEE Trans. Image Process., vol. 29, p. 3993–4002, 2020. doi:10.1109/TIP.2019.2963389
[BibTeX] [Download PDF]@article{gholami19tip, author = {Behnam Gholami and Pritish Sahu and Ognjen Rudovic and Konstantinos Bousmalis and Vladimir Pavlovic}, title = {Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach}, journal = {{IEEE} Trans. Image Process.}, volume = {29}, pages = {3993--4002}, year = {2020}, url = {https://doi.org/10.1109/TIP.2019.2963389}, doi = {10.1109/TIP.2019.2963389}, timestamp = {Sat, 30 May 2020 19:54:53 +0200}, biburl = {https://dblp.org/rec/journals/tip/GholamiSRBP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2019
- M. Kim, Y. Wang, P. Sahu, and V. Pavlovic, “Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement,” in IEEE International Conference on Computer Vision, ICCV, Seoul, Korea, 2019.
[BibTeX]@inproceedings{kim19iccv, address = {Seoul, Korea}, author = {Minyoung Kim and Yuting Wang and Pritish Sahu and Vladimir Pavlovic}, booktitle = {{IEEE} International Conference on Computer Vision, {ICCV}}, date-added = {2019-09-05 20:58:51 +0100}, date-modified = {2019-09-05 21:00:05 +0100}, month = oct, title = {Bayes-Factor-{VAE}: Hierarchical {Bayesian} Deep Auto-Encoder Models for Factor Disentanglement}, year = {2019} } - B. Gholami, P. Sahu, M. Kim, and V. Pavlovic, “Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation,” in IEEE International Conference on Computer Vision, ICCV, 6th Workshop on Transferring and Adapting Source Knowledge in Computer Vision, Seoul, Korea, 2019.
[BibTeX]@inproceedings{gholami19iccvws, address = {Seoul, Korea}, author = {Behnam Gholami and Pritish Sahu and Minyoung Kim and Vladimir Pavlovic}, booktitle = {{IEEE} International Conference on Computer Vision, {ICCV}, 6th Workshop on Transferring and Adapting Source Knowledge in Computer Vision}, date-added = {2019-09-05 20:54:25 +0100}, date-modified = {2019-09-05 20:57:09 +0100}, month = oct, title = {Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation}, year = {2019} } - M. Kim, Y. Wang, P. Sahu, and V. Pavlovic, “Relevance Factor VAE: Learning and Identifying Disentangled Factors,” CoRR, vol. abs/1902.01568, 2019.
[BibTeX]@article{kim19rfvae_arxiv, author = {Minyoung Kim and Yuting Wang and Pritish Sahu and Vladimir Pavlovic}, journal = {CoRR}, title = {Relevance Factor {VAE:} Learning and Identifying Disentangled Factors}, volume = {abs/1902.01568}, year = {2019} } - M. Kim, P. Sahu, B. Gholami, and V. Pavlovic, “Unsupervised visual domain adaptation: A deep max-margin Gaussian process approach,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, p. 4380–4390.
[BibTeX]@inproceedings{kim2019ugpda, author = {Kim, Minyoung and Sahu, Pritish and Gholami, Behnam and Pavlovic, Vladimir}, booktitle = {Proceedings of the {IEEE} Conference on Computer Vision and Pattern Recognition}, pages = {4380--4390}, title = {Unsupervised visual domain adaptation: A deep max-margin {Gaussian} process approach}, year = {2019} } - M. Kim, P. Sahu, B. Gholami, and V. Pavlovic, “Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach,” CoRR, vol. abs/1902.08727, 2019.
[BibTeX]@article{kim19ugpda_arxiv, author = {Minyoung Kim and Pritish Sahu and Behnam Gholami and Vladimir Pavlovic}, journal = {CoRR}, title = {Unsupervised Visual Domain Adaptation: {A} Deep Max-Margin {Gaussian} Process Approach}, volume = {abs/1902.08727}, year = {2019} }
2018
- B. Gholami, P. Sahu, O. Rudovic, K. Bousmalis, and V. Pavlovic, “Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach,” CoRR, vol. abs/1810.11547, 2018.
[BibTeX]@article{behnam18umtda_arxiv, author = {Behnam Gholami and Pritish Sahu and Ognjen Rudovic and Konstantinos Bousmalis and Vladimir Pavlovic}, journal = {CoRR}, title = {Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach}, volume = {abs/1810.11547}, year = {2018} }
2016
- S. Yoon, M. Kapadia, P. Sahu, and V. Pavlovic, “Filling in the Blanks: Reconstructing Microscopic Crowd Motion from Multiple Disparate Noisy Sensors,” in 2016 IEEE Winter Applications of Computer Vision Workshops, WACV 2016 Workshops, 2016, p. 1–9. doi:10.1109/wacvw.2016.7470118
[BibTeX]@inproceedings{yoon16wacvws, author = {Sejong Yoon and Mubbasir Kapadia and Pritish Sahu and Vladimir Pavlovic}, booktitle = {2016 {IEEE} Winter Applications of Computer Vision Workshops, {WACV} 2016 Workshops}, date-added = {2016-02-18 13:43:36 +0000}, date-modified = {2016-09-11 21:17:46 +0000}, doi = {10.1109/wacvw.2016.7470118}, month = mar, note = {25% contribution.}, pages = {1--9}, title = {Filling in the Blanks: Reconstructing Microscopic Crowd Motion from Multiple Disparate Noisy Sensors}, year = {2016}, bdsk-url-1 = {https://doi.org/10.1109/wacvw.2016.7470118} }