96 citations · 362 across the 15 of their papers we have counts for
4 papers · 1 filter
Scaling Vision with Sparse Mixture of Experts
Carlos Riquelme, Joan Puigcerver, Basil Mustafa +5
Sparsely-gated Mixture of Experts networks (MoEs) have demonstrated excellent scalability in Natural Language Processing. In Computer Vision, however, almost all performant network…
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…
Supervised Transfer Learning at Scale for Medical Imaging
Basil Mustafa, Aaron Loh, Jan Freyberg +12
Transfer learning is a standard technique to improve performance on tasks with limited data. However, for medical imaging, the value of transfer learning is less clear. This is lik…
Big Self-Supervised Models Advance Medical Image Classification
Shekoofeh Azizi, Basil Mustafa, Fiona Ryan +9
Self-supervised pretraining followed by supervised fine-tuning has seen success in image recognition, especially when labeled examples are scarce, but has received limited attentio…