Jay Nandy

20 papers A* 3A 2B 4C 1Journal 9Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
PLGC: Pseudo-Labeled Graph Condensation.
CoRR
Jay Nandy, Arnab Kumar Mondal, Anuj Rathore, Mahesh Chandran
2024 A* conf
Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples.
AAAI
Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer
2024 — conf
Stochastic Experience-Replay for Graph Continual Learning.
LoG
Arnab Kumar Mondal, Jay Nandy, Manohar Kaul, Mahesh Chandran
2024 J jnl
Teacher-Guided Graph Contrastive Learning.
Trans. Mach. Learn. Res.
Jay Nandy, Arnab Kumar Mondal, Manohar Kaul, Prathosh AP
2023 J jnl
Improving Fairness-Accuracy tradeoff with few Test Samples under Covariate Shift.
CoRR
Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer
2023 A conf
Non-Uniform Adversarial Perturbations for Discrete Tabular Datasets.
CIKM
Jay Nandy, Jatin Chauhan, Rishi Saket, Aravindan Raghuveer
2022 C conf
Compact Feature Representation for Unsupervised Ood Detection.
IGARSS
Sudipan Saha, Jakob Gawlikowski, Jay Nandy, Xiao Xiang Zhu
2022 A conf
Domain-Agnostic Contrastive Representations for Learning from Label Proportions.
CIKM
Jay Nandy, Rishi Saket, Prateek Jain, Jatin Chauhan, Balaraman Ravindran, Aravindan Raghuveer
2022 A* conf
Multi-Variate Time Series Forecasting on Variable Subsets.
KDD
Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran
2022 J jnl
Multi-Variate Time Series Forecasting on Variable Subsets.
CoRR
Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran
2021 J jnl
Adversarially Robust Classifier with Covariate Shift Adaptation.
CoRR
Jay Nandy, Sudipan Saha, Wynne Hsu, Mong-Li Lee, Xiao Xiang Zhu
2021 B conf
Distributional Shifts In Automated Diabetic Retinopathy Screening.
ICIP
Jay Nandy, Wynne Hsu, Mong-Li Lee
2021 J jnl
Distributional Shifts in Automated Diabetic Retinopathy Screening.
CoRR
Jay Nandy, Wynne Hsu, Mong-Li Lee
2020 B conf
Approximate Manifold Defense Against Multiple Adversarial Perturbations.
IJCNN
Jay Nandy, Wynne Hsu, Mong-Li Lee
2020 J jnl
Approximate Manifold Defense Against Multiple Adversarial Perturbations.
CoRR
Jay Nandy, Wynne Hsu, Mong-Li Lee
2020 A* conf
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples.
NeurIPS
Jay Nandy, Wynne Hsu, Mong-Li Lee
2020 J jnl
Towards Maximizing the Representation Gap between In-Domain \& Out-of-Distribution Examples.
CoRR
Jay Nandy, Wynne Hsu, Mong-Li Lee
2018 B conf
Normal Similarity Network for Generative Modelling.
ICIP
Jay Nandy, Wynne Hsu, Mong-Li Lee
2018 J jnl
Normal Similarity Network for Generative Modelling.
CoRR
Jay Nandy, Wynne Hsu, Mong-Li Lee
2016 B conf
An Incremental Feature Extraction Framework for Referable Diabetic Retinopathy Detection.
ICTAI
Jay Nandy, Wynne Hsu, Mong-Li Lee