Attention-based deep multiple instance learning M Ilse, J Tomczak, M Welling International conference on machine learning, 2127-2136, 2018 | 2022 | 2018 |
Diva: Domain invariant variational autoencoders M Ilse, JM Tomczak, C Louizos, M Welling Medical Imaging with Deep Learning, 322-348, 2020 | 230 | 2020 |
Learning to exploit temporal structure for biomedical vision-language processing S Bannur, S Hyland, Q Liu, F Perez-Garcia, M Ilse, DC Castro, B Boecking, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 96 | 2023 |
Selecting data augmentation for simulating interventions M Ilse, JM Tomczak, P Forré International Conference on Machine Learning, 4555-4562, 2021 | 83* | 2021 |
Deep multiple instance learning for digital histopathology M Ilse, JM Tomczak, M Welling Handbook of Medical Image Computing and Computer Assisted Intervention, 521-546, 2020 | 49 | 2020 |
Combining interventional and observational data using causal reductions M Ilse, P Forré, M Welling, JM Mooij arXiv preprint arXiv:2103.04786, 2021 | 17* | 2021 |
Histopathological classification of precursor lesions of esophageal adenocarcinoma: A deep multiple instance learning approach JM Tomczak, M Ilse, M Welling, M Jansen, HG Coleman, M Lucas, ... | 15* | 2018 |
Deep learning with permutation-invariant operator for multi-instance histopathology classification JM Tomczak, M Ilse, M Welling arXiv preprint arXiv:1712.00310, 2017 | 14 | 2017 |
MAIRA-2: Grounded Radiology Report Generation S Bannur, K Bouzid, DC Castro, A Schwaighofer, S Bond-Taylor, M Ilse, ... arXiv e-prints, arXiv: 2406.04449, 2024 | 11 | 2024 |
RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision F Pérez-García, H Sharma, S Bond-Taylor, K Bouzid, V Salvatelli, M Ilse, ... arXiv preprint arXiv:2401.10815, 2024 | 11 | 2024 |
AIRIVA: a deep generative model of adaptive immune repertoires MF Pradier, N Prasad, P Chapfuwa, S Ghalebikesabi, M Ilse, ... Machine Learning for Healthcare Conference, 588-611, 2023 | 7 | 2023 |
Problems using deep generative models for probabilistic audio source separation M Frank, M Ilse PMLR, 2020 | 4 | 2020 |
Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology K Bouzid, H Sharma, S Killcoyne, DC Castro, A Schwaighofer, M Ilse, ... Nature Communications 15 (1), 2026, 2024 | 3 | 2024 |
RadEdit: stress-testing biomedical vision models via diffusion image editing F Pérez-García, S Bond-Taylor, PP Sanchez, B van Breugel, DC Castro, ... arXiv preprint arXiv:2312.12865, 2023 | 3 | 2023 |
Invariance in deep representations M Ilse | | 2022 |