1 code implementation • 30 Jun 2022 • Joona Pohjonen, Carolin Stürenberg, Atte Föhr, Reija Randen-Brady, Lassi Luomala, Jouni Lohi, Esa Pitkänen, Antti Rannikko, Tuomas Mirtti
How to recognize models suffering from this fragility, and how to design robust models are the main obstacles to clinical adoption.
no code implementations • 16 Jun 2022 • Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramon Vinas Torne, Evis Sala, Pietro Lio, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb
Classifying samples in incomplete datasets is a common aim for machine learning practitioners, but is non-trivial.
no code implementations • 31 Mar 2021 • Joona Pohjonen, Carolin Stürenberg, Antti Rannikko, Tuomas Mirtti, Esa Pitkänen
We show that spectral decoupling allows training neural networks on datasets with strong spurious correlations and increases networks' robustness for data distribution shifts.
no code implementations • 14 Mar 2019 • Umair Akhtar Hasan Khan, Carolin Stürenberg, Oguzhan Gencoglu, Kevin Sandeman, Timo Heikkinen, Antti Rannikko, Tuomas Mirtti
We validate our approach on annotated prostate whole slide images by using a publicly available breast histopathology dataset as pre-training.