| Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels E Englesson, H Azizpour NeurIPS, 2021 | 121 | 2021 |
| Consistency Regularization can Improve Robustness to Label Noise E Englesson, H Azizpour ICML, Workshop, 2021 | 29 | 2021 |
| Deep Double Descent via Smooth Interpolation M Gamba, E Englesson, M Björkman, H Azizpour TMLR, 2023 | 13 | 2023 |
| Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation E Englesson, H Azizpour ICML, Workshop, 2019 | 12 | 2019 |
| Robust Classification via Regression for Learning with Noisy Labels E Englesson, H Azizpour ICLR, 2023 | 6 | 2023 |
| Indirectly Parameterized Concrete Autoencoders A Nilsson, K Wijk, E Englesson, A Hotti, C Saccardi, O Kviman, ... ICML, 2024 | 3 | 2024 |
| Logistic-Normal Likelihoods for Heteroscedastic Label Noise E Englesson, A Mehrpanah, H Azizpour TMLR, 2023 | 2 | 2023 |
| Medical Image Segmentation with SAM-generated Annotations I Häkkinen, I Melekhov, E Englesson, H Azizpour, J Kannala ECCV, Workshop, 2024 | | 2024 |
| On Spectral Properties of Gradient-based Explanation Methods A Mehrpanah, E Englesson, H Azizpour ECCV, 2024 | | 2024 |
| On Label Noise in Image Classification: An Aleatoric Uncertainty Perspective E Englesson KTH Royal Institute of Technology, 2024 | | 2024 |
Hossein AzizpourAssociate Professor, KTH (Royal Institute of Technology)Verified email at kth.se
