96 citations · 198 across the 7 of their papers we have counts for
4 papers · 1 filter
Correlated Input-Dependent Label Noise in Large-Scale Image Classification
Mark Collier, Basil Mustafa, Efi Kokiopoulou +2
Large scale image classification datasets often contain noisy labels. We take a principled probabilistic approach to modelling input-dependent, also known as heteroscedastic, label…
Deep Ensembles for Low-Data Transfer Learning
Basil Mustafa, Carlos Riquelme, Joan Puigcerver +3
In the low-data regime, it is difficult to train good supervised models from scratch. Instead practitioners turn to pre-trained models, leveraging transfer learning. Ensembling is…
Scalable Transfer Learning with Expert Models
Joan Puigcerver, Carlos Riquelme, Basil Mustafa +5
Transfer of pre-trained representations can improve sample efficiency and reduce computational requirements for new tasks. However, representations used for transfer are usually ge…
A Simple Probabilistic Method for Deep Classification under Input-Dependent Label Noise
Mark Collier, Basil Mustafa, Efi Kokiopoulou +2
Datasets with noisy labels are a common occurrence in practical applications of classification methods. We propose a simple probabilistic method for training deep classifiers under…