| Pi-net: A deep learning approach to extract topological persistence images A Som, H Choi, KN Ramamurthy, MP Buman, P Turaga Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 25 | 2020 |
| AMC-loss: Angular margin contrastive loss for improved explainability in image classification H Choi, A Som, P Turaga Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 21 | 2020 |
| Temporal alignment improves feature quality: an experiment on activity recognition with accelerometer data H Choi, Q Wang, M Toledo, P Turaga, M Buman, A Srivastava Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 10 | 2018 |
| Role of orthogonality constraints in improving properties of deep networks for image classification H Choi, A Som, P Turaga arXiv preprint arXiv:2009.10762, 2020 | 6 | 2020 |
| Interpretable COVID-19 chest x-ray classification via orthogonality constraint EY Wang, A Som, A Shukla, H Choi, P Turaga arXiv preprint arXiv:2102.08360, 2021 | 3 | 2021 |
| Leveraging angular distributions for improved knowledge distillation ES Jeon, H Choi, A Shukla, P Turaga Neurocomputing 518, 466-481, 2023 | 1 | 2023 |
| Leveraging Angular Distributions for Improved Knowledge Distillation E Som Jeon, H Choi, A Shukla, P Turaga arXiv e-prints, arXiv: 2302.14130, 2023 | | 2023 |
| Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study H Choi, ES Jeon, A Shukla, P Turaga WACV 2023, arXiv preprint arXiv:2211.03946, 2022 | | 2022 |
| Topological Knowledge Distillation for Wearable Sensor Data ES Jeon, H Choi, A Shukla, Y Wang, MP Buman, P Turaga 2022 56th Asilomar Conference on Signals, Systems, and Computers, 837-842, 2022 | | 2022 |
| Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study (Supplementary Material) H Choi, ES Jeon, A Shukla, P Turaga | | |
| Interpretable COVID-19 Chest X-Ray Classification via Orthogonality Constraint (preprint) E Wang, A Som, A Shukla, H Choi, P Turaga | | |
