| A closer look at smoothness in domain adversarial training H Rangwani, SK Aithal, M Mishra, A Jain, VB Radhakrishnan International conference on machine learning, 18378-18399, 2022 | 88 | 2022 |
| S3vaada: Submodular subset selection for virtual adversarial active domain adaptation H Rangwani, A Jain, SK Aithal, RV Babu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 24 | 2021 |
| Methods and analysis of the first competition in predicting generalization of deep learning Y Jiang, P Natekar, M Sharma, SK Aithal, D Kashyap, N Subramanyam, ... NeurIPS 2020 Competition and Demonstration Track, 170-190, 2021 | 21 | 2021 |
| Escaping saddle points for effective generalization on class-imbalanced data H Rangwani, SK Aithal, M Mishra Advances in Neural Information Processing Systems 35, 22791-22805, 2022 | 17 | 2022 |
| Robustness to Augmentations as a Generalization metric SK Aithal, D Kashyap, N Subramanyam arXiv preprint arXiv:2101.06459, 2021 | 15 | 2021 |
| Towards domain adversarial methods to mitigate texture bias D Kashyap, SK Aithal, C Rakshith, N Subramanyam ICML 2022: Workshop on Spurious Correlations, Invariance and Stability, 2022 | 3 | 2022 |
| Depth-Guided Self-Supervised Learning: Seeing the World in 3D SK Aithal, A Goyal, A Lamb, Y Bengio, MC Mozer | | 2023 |
| Leveraging the Third Dimension in Contrastive Learning S Aithal, A Goyal, A Lamb, Y Bengio, M Mozer arXiv preprint arXiv:2301.11790, 2023 | | 2023 |
| A Limitations of Our Work H Rangwani, SK Aithal, M Mishra, RV Babu | | |
