An Incremental Feature Extraction Framework for Referable Diabetic Retinopathy Detection. - Jay Nandy; Wynne Hsu; Mong-Li Lee (ICTAI, 2016)

Normal Similarity Network for Generative Modelling. - Jay Nandy; Wynne Hsu; Mong-Li Lee (ICIP, 2018)

Approximate Manifold Defense Against Multiple Adversarial Perturbations. - Jay Nandy; Wynne Hsu; Mong-Li Lee (IJCNN, 2020)

Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples. - Jay Nandy; Wynne Hsu; Mong-Li Lee (NeurIPS, 2020)

Distributional Shifts In Automated Diabetic Retinopathy Screening. - Jay Nandy; Wynne Hsu; Mong-Li Lee (ICIP, 2021)

Adversarially Robust Classifier with Covariate Shift Adaptation. - Jay Nandy; Sudipan Saha; Wynne Hsu; Mong-Li Lee; Xiao Xiang Zhu 001 (CoRR, 2021)

Domain-Agnostic Contrastive Representations for Learning from Label Proportions. - Jay Nandy; Rishi Saket; Prateek Jain; Jatin Chauhan; Balaraman Ravindran; Aravindan Raghuveer (CIKM, 2022)

Compact Feature Representation for Unsupervised Ood Detection. - Sudipan Saha; Jakob Gawlikowski; Jay Nandy; Xiao Xiang Zhu 001 (IGARSS, 2022)

Multi-Variate Time Series Forecasting on Variable Subsets. - Jatin Chauhan; Aravindan Raghuveer; Rishi Saket; Jay Nandy; Balaraman Ravindran (KDD, 2022)

Non-Uniform Adversarial Perturbations for Discrete Tabular Datasets. - Jay Nandy; Jatin Chauhan; Rishi Saket; Aravindan Raghuveer (CIKM, 2023)

Improving Fairness-Accuracy tradeoff with few Test Samples under Covariate Shift. - Shreyas Havaldar; Jatin Chauhan; Karthikeyan Shanmugam; Jay Nandy; Aravindan Raghuveer (CoRR, 2023)

Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples. - Shreyas Havaldar; Jatin Chauhan; Karthikeyan Shanmugam; Jay Nandy; Aravindan Raghuveer (AAAI, 2024)

Stochastic Experience-Replay for Graph Continual Learning. - Arnab Kumar Mondal; Jay Nandy; Manohar Kaul; Mahesh Chandran (LoG, 2024)

Teacher-Guided Graph Contrastive Learning. - Jay Nandy; Arnab Kumar Mondal; Manohar Kaul; Prathosh AP (Trans. Mach. Learn. Res., 2024)