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2020 – today
- 2024
[c2]Evangelia Christodoulou, Annika Reinke, Rola Houhou, Piotr Kalinowski, Selen Erkan, Carole H. Sudre, Ninon Burgos, Sofiène Boutaj, Sophie Loizillon, Maëlys Solal, Nicola Rieke, Veronika Cheplygina, Michela Antonelli, Leon D. Mayer, Minu Dietlinde Tizabi, M. Jorge Cardoso, Amber L. Simpson, Paul F. Jäger, Annette Kopp-Schneider, Gaël Varoquaux, Olivier Colliot, Lena Maier-Hein:
Confidence Intervals Uncovered: Are We Ready for Real-World Medical Imaging AI? MICCAI (10) 2024: 124-132- [i3]Ravi Hassanaly, Camille Brianceau, Maëlys Solal, Olivier Colliot, Ninon Burgos:
Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET. CoRR abs/2401.16363 (2024) - 2023
- [i2]Maëlys Solal, Andrew Jesson, Yarin Gal, Alyson Douglas:
Using uncertainty-aware machine learning models to study aerosol-cloud interactions. CoRR abs/2301.11921 (2023) - [i1]Maëlys Solal, Ravi Hassanaly, Ninon Burgos:
Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET. CoRR abs/2311.12081 (2023) - 2022
- [c1]Andrew Jesson, Alyson Douglas, Peter Manshausen, Maëlys Solal, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit:
Scalable Sensitivity and Uncertainty Analyses for Causal-Effect Estimates of Continuous-Valued Interventions. NeurIPS 2022
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