Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation. - Erik Englesson; Hossein Azizpour (CoRR, 2019)

Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels. - Erik Englesson; Hossein Azizpour (NeurIPS, 2021)

Consistency Regularization Can Improve Robustness to Label Noise. - Erik Englesson; Hossein Azizpour (CoRR, 2021)

Logistic-Normal Likelihoods for Heteroscedastic Label Noise in Classification. - Erik Englesson; Amir Mehrpanah; Hossein Azizpour (CoRR, 2023)

Logistic-Normal Likelihoods for Heteroscedastic Label Noise. - Erik Englesson; Amir Mehrpanah; Hossein Azizpour (Trans. Mach. Learn. Res., 2023)

Deep Double Descent via Smooth Interpolation. - Matteo Gamba; Erik Englesson; Mårten Björkman; Hossein Azizpour (Trans. Mach. Learn. Res., 2023)

Medical Image Segmentation with SAM-Generated Annotations. - Iira Häkkinen; Iaroslav Melekhov; Erik Englesson; Hossein Azizpour; Juho Kannala (ECCV Workshops (22), 2024)

On Spectral Properties of Gradient-Based Explanation Methods. - Amir Mehrpanah; Erik Englesson; Hossein Azizpour (ECCV (87), 2024)

Robust Classification via Regression for Learning with Noisy Labels. - Erik Englesson; Hossein Azizpour (ICLR, 2024)

Indirectly Parameterized Concrete Autoencoders. - Alfred Nilsson; Klas Wijk; Sai Bharath Chandra Gutha; Erik Englesson; Alexandra Hotti; Carlo Saccardi; Oskar Kviman; Jens Lagergren; Ricardo Vinuesa; Hossein Azizpour (ICML, 2024)