| Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples J Nandy, W Hsu, ML Lee arXiv preprint arXiv:2010.10474, 2020 | 102 | 2020 |
| KDDclus: A simple method for multi-density clustering S Mitra, J Nandy Proceedings of International Workshop on Soft Computing Applications and …, 2011 | 33 | 2011 |
| Multi-variate time series forecasting on variable subsets J Chauhan, A Raghuveer, R Saket, J Nandy, B Ravindran Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 31 | 2022 |
| An incremental feature extraction framework for referable diabetic retinopathy detection J Nandy, W Hsu, ML Lee 2016 IEEE 28th International Conference on Tools with Artificial …, 2016 | 18 | 2016 |
| Approximate manifold defense against multiple adversarial perturbations J Nandy, W Hsu, ML Lee 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 15 | 2020 |
| Towards bridging the gap between empirical and certified robustness against adversarial examples J Nandy, S Saha, W Hsu, ML Lee, XX Zhu arXiv preprint arXiv:2102.05096, 2021 | 13* | 2021 |
| Domain-agnostic contrastive representations for learning from label proportions J Nandy, R Saket, P Jain, J Chauhan, B Ravindran, A Raghuveer Proceedings of the 31st ACM International Conference on Information …, 2022 | 11 | 2022 |
| Distributional Shifts In Automated Diabetic Retinopathy Screening J Nandy, W Hsu, ML Lee 2021 IEEE International Conference on Image Processing (ICIP), 255-259, 2021 | 6 | 2021 |
| Fairness under covariate shift: Improving fairness-accuracy tradeoff with few unlabeled test samples S Havaldar, J Chauhan, K Shanmugam, J Nandy, A Raghuveer Proceedings of the AAAI Conference on Artificial Intelligence 38 (11), 12331 …, 2024 | 5* | 2024 |
| Non-uniform adversarial perturbations for discrete tabular datasets J Nandy, J Chauhan, R Saket, A Raghuveer Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 5 | 2023 |
| Normal similarity network for generative modelling J Nandy, W Hsu, ML Lee 2018 25th IEEE International Conference on Image Processing (ICIP), 1817-1821, 2018 | 4 | 2018 |
| Stochastic Experience-Replay for Graph Continual Learning AK Mondal, J Nandy, M Kaul, M Chandran The Third Learning on Graphs Conference, 2024 | 3 | 2024 |
| Compact Feature Representation for Unsupervised Ood Detection S Saha, J Gawlikowski, J Nandy, XX Zhu IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium …, 2022 | 2 | 2022 |
| Teacher-Guided Graph Contrastive Learning J Nandy, AK Mondal, M Kaul, P AP Transactions on Machine Learning Research, 2024 | 1 | 2024 |
| Robustness and Uncertainty Estimation for Deep Neural Networks J Nandy PQDT-Global, 2021 | 1 | 2021 |
| PLGC: Pseudo-Labeled Graph Condensation J Nandy, AK Mondal, A Rathore, M Chandran arXiv preprint arXiv:2601.10358, 2026 | | 2026 |
| Condensed graph distribution (cgd)-based graph continual learning J Nandy, AK MONDAL US Patent App. 19/081,045, 2025 | | 2025 |
| Graph representations AK MONDAL, J Nandy US Patent App. 18/796,439, 2025 | | 2025 |
Wynne HSUProfessor of Computer Science, National Univeristy of SingaporeVerified email at comp.nus.edu.sg
