PLGC: Pseudo-Labeled Graph Condensation.

Jay Nandy

Jay Nandy Arnab Kumar Mondal Anuj Rathore Mahesh Chandran PLGC: Pseudo-Labeled Graph Condensation. 2026 January abs/2601.10358 CoRR https://doi.org/10.48550/arXiv.2601.10358 db/journals/corr/corr2601.html#abs-2601-10358 streams/journals/corr

Jay Nandy Arnab Kumar Mondal Manohar Kaul Prathosh AP Teacher-Guided Graph Contrastive Learning. 2024 2024 Trans. Mach. Learn. Res. https://openreview.net/forum?id=15tjpSHI15 db/journals/tmlr/tmlr2024.html#NandyMKA24

Shreyas Havaldar Jatin Chauhan Karthikeyan Shanmugam 0001 Jay Nandy Aravindan Raghuveer Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples. 12331-12339 2024 AAAI https://doi.org/10.1609/aaai.v38i11.29124 conf/aaai/2024 db/conf/aaai/aaai2024.html#HavaldarCSNR24 Arnab Kumar Mondal Jay Nandy Manohar Kaul Mahesh Chandran Stochastic Experience-Replay for Graph Continual Learning. 32 2024 LoG https://proceedings.mlr.press/v269/mondal25a.html conf/log/2024 db/conf/log/log2024.html#MondalNKC24 streams/conf/log Jay Nandy Jatin Chauhan Rishi Saket Aravindan Raghuveer Non-Uniform Adversarial Perturbations for Discrete Tabular Datasets. 1887-1896 2023 CIKM https://doi.org/10.1145/3583780.3614992 conf/cikm/2023 db/conf/cikm/cikm2023.html#NandyCSR23

Shreyas Havaldar Jatin Chauhan Karthikeyan Shanmugam 0001 Jay Nandy Aravindan Raghuveer Improving Fairness-Accuracy tradeoff with few Test Samples under Covariate Shift. 2023 abs/2310.07535 CoRR https://doi.org/10.48550/arXiv.2310.07535 db/journals/corr/corr2310.html#abs-2310-07535

Jay Nandy Rishi Saket Prateek Jain Jatin Chauhan Balaraman Ravindran Aravindan Raghuveer Domain-Agnostic Contrastive Representations for Learning from Label Proportions. 1542-1551 2022 CIKM https://doi.org/10.1145/3511808.3557293 conf/cikm/2022 db/conf/cikm/cikm2022.html#NandySJCRR22 Sudipan Saha Jakob Gawlikowski Jay Nandy Xiao Xiang Zhu 0001 Compact Feature Representation for Unsupervised Ood Detection. 3143-3146 2022 IGARSS https://doi.org/10.1109/IGARSS46834.2022.9884481 conf/igarss/2022 db/conf/igarss/igarss2022.html#SahaGNZ22 Jatin Chauhan Aravindan Raghuveer Rishi Saket Jay Nandy Balaraman Ravindran Multi-Variate Time Series Forecasting on Variable Subsets. 76-86 2022 KDD https://doi.org/10.1145/3534678.3539394 conf/kdd/2022 db/conf/kdd/kdd2022.html#ChauhanRSNR22

Jatin Chauhan Aravindan Raghuveer Rishi Saket Jay Nandy Balaraman Ravindran Multi-Variate Time Series Forecasting on Variable Subsets. 2022 abs/2206.12626 CoRR https://doi.org/10.48550/arXiv.2206.12626 db/journals/corr/corr2206.html#abs-2206-12626

Jay Nandy Wynne Hsu Mong-Li Lee Distributional Shifts In Automated Diabetic Retinopathy Screening. 255-259 2021 ICIP https://doi.org/10.1109/ICIP42928.2021.9506635 conf/icip/2021 db/conf/icip/icip2021.html#NandyHL21

Jay Nandy Sudipan Saha Wynne Hsu Mong-Li Lee Xiao Xiang Zhu 0001 Adversarially Robust Classifier with Covariate Shift Adaptation. 2021 abs/2102.05096 CoRR https://arxiv.org/abs/2102.05096 db/journals/corr/corr2102.html#abs-2102-05096

Jay Nandy Wynne Hsu Mong-Li Lee Distributional Shifts in Automated Diabetic Retinopathy Screening. 2021 abs/2107.11822 CoRR https://arxiv.org/abs/2107.11822 db/journals/corr/corr2107.html#abs-2107-11822

Jay Nandy Wynne Hsu Mong-Li Lee Approximate Manifold Defense Against Multiple Adversarial Perturbations. 1-8 2020 IJCNN https://doi.org/10.1109/IJCNN48605.2020.9207312 conf/ijcnn/2020 db/conf/ijcnn/ijcnn2020.html#NandyHL20 Jay Nandy Wynne Hsu Mong-Li Lee Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples. 2020 NeurIPS https://proceedings.neurips.cc/paper/2020/hash/68d3743587f71fbaa5062152985aff40-Abstract.html conf/nips/2020 db/conf/nips/neurips2020.html#NandyHL20

Jay Nandy Wynne Hsu Mong-Li Lee Approximate Manifold Defense Against Multiple Adversarial Perturbations. 2020 abs/2004.02183 CoRR https://arxiv.org/abs/2004.02183 db/journals/corr/corr2004.html#abs-2004-02183

Jay Nandy Wynne Hsu Mong-Li Lee Towards Maximizing the Representation Gap between In-Domain \& Out-of-Distribution Examples. 2020 abs/2010.10474 CoRR https://arxiv.org/abs/2010.10474 db/journals/corr/corr2010.html#abs-2010-10474

Jay Nandy Wynne Hsu Mong-Li Lee Normal Similarity Network for Generative Modelling. 1817-1821 2018 ICIP https://doi.org/10.1109/ICIP.2018.8451432 conf/icip/2018 db/conf/icip/icip2018.html#NandyHL18

Jay Nandy Wynne Hsu Mong-Li Lee Normal Similarity Network for Generative Modelling. 2018 abs/1805.05269 CoRR http://arxiv.org/abs/1805.05269 db/journals/corr/corr1805.html#abs-1805-05269

Jay Nandy Wynne Hsu Mong-Li Lee An Incremental Feature Extraction Framework for Referable Diabetic Retinopathy Detection. 908-912 2016 ICTAI https://doi.org/10.1109/ICTAI.2016.0140 https://doi.ieeecomputersociety.org/10.1109/ICTAI.2016.0140 conf/ictai/2016 db/conf/ictai/ictai2016.html#NandyHL16 Mahesh Chandran Jatin Chauhan Jakob Gawlikowski Shreyas Havaldar Wynne Hsu Prateek Jain Manohar Kaul Mong-Li Lee Arnab Kumar Mondal Prathosh A. P.Prathosh AP Aravindan Raghuveer Anuj Rathore Balaraman Ravindran Sudipan Saha Rishi Saket Karthikeyan Shanmugam 0001 Xiao Xiang Zhu 0001