Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations N Marini, S Marchesin, S Otálora, M Wodzinski, A Caputo, ... NPJ digital medicine 5 (1), 102, 2022 | 50 | 2022 |
Time series classification in reservoir-and model-space W Aswolinskiy, RF Reinhart, J Steil Neural Processing Letters 48 (2), 789-809, 2018 | 30 | 2018 |
Time series classification in reservoir-and model-space: a comparison W Aswolinskiy, RF Reinhart, J Steil Artificial Neural Networks in Pattern Recognition: 7th IAPR TC3 Workshop …, 2016 | 25 | 2016 |
RM-SORN: a reward-modulated self-organizing recurrent neural network W Aswolinskiy, G Pipa Frontiers in computational neuroscience 9, 36, 2015 | 24 | 2015 |
Neural image compression for non-small cell lung cancer subtype classification in H&E stained whole-slide images W Aswolinskiy, D Tellez, G Raya, L van der Woude, M Looijen-Salamon, ... Medical Imaging 2021: Digital Pathology 11603, 1160304, 2021 | 17 | 2021 |
Impact of Regularization on the Model Space for Time Series Classification W Aswolinskiy, RF Reinhart, J Steil Workshop New Challenges in Neural Computation, 2015 | 16 | 2015 |
Gigapixel end-to-end training using streaming and attention S Dooper, H Pinckaers, W Aswolinskiy, K Hebeda, S Jarkman, ... Medical Image Analysis 88, 102881, 2023 | 14 | 2023 |
Unsupervised transfer learning for time series via self-predictive modelling-first results W Aswolinskiy, B Hammer Proceedings of the Workshop on New Challenges in Neural Computation (NC2) 3, 2017 | 11 | 2017 |
Caption generation from histopathology whole-slide images using pre-trained transformers BC Guevara, N Marini, S Marchesin, W Aswolinskiy, RJ Schlimbach, ... Medical Imaging with Deep Learning, short paper track, 2023 | 9 | 2023 |
Modelling of parameterized processes via regression in the model space W Aswolinskiy, F Reinhart, JJ Steil Proceedings of 24th European Symposium on Artificial Neural Networks, 2016 | 9 | 2016 |
Detection and subtyping of basal cell carcinoma in whole-slide histopathology using weakly-supervised learning DJ Geijs, S Dooper, W Aswolinskiy, LM Hillen, AL Amir, G Litjens Medical Image Analysis 93, 103063, 2024 | 7 | 2024 |
Modelling of parametrized processes via regression in the model space of neural networks W Aswolinskiy, RF Reinhart, JJ Steil Neurocomputing 268, 55-63, 2017 | 7 | 2017 |
Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations. NPJ Digit. Med. 5 (1), 1–18 (2022) N Marini, S Marchesin, S Otlora, M Wodzinski, A Caputo, M Van Rijthoven, ... | 7 | |
PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning W Aswolinskiy, E Munari, HM Horlings, L Mulder, G Bogina, J Sanders, ... Breast Cancer Research 25 (1), 142, 2023 | 4 | 2023 |
Maschinelles lernen in technischen systemen F Reinhart, K Neumann, W Aswolinskiy, J Steil, B Hammer Steigerung der Intelligenz mechatronischer Systeme, 73-118, 2018 | 4 | 2018 |
Learning in the model space of neural networks W Aswolinskiy | 3 | 2018 |
Impact of Layer Selection in Histopathology Foundation Models on Downstream Task Performance W Aswolinskiy, M Paulikat, C Aichmueller Medical Imaging with Deep Learning, 2024 | 1 | 2024 |
Parameterized pattern generation via regression in the model space of echo state networks W Aswolinskiy, JJ Steil Proceedings of the Workshop on New Challenges in Neural Computation, 2016 | 1 | 2016 |
Classifying histopathological growth patterns for resected colorectal liver metastasis with a deep learning analysis DJ Höppener, W Aswolinskiy, Z Qian, D Tellez, PMH Nierop, M Starmans, ... BJS open 8 (6), zrae127, 2024 | | 2024 |
Benchmarking Hierarchical Image Pyramid Transformer for the classification of colon biopsies and polyps in histopathology images NSL Contreras, M D'Amato, F Ciompi, C Grisi, W Aswolinskiy, S Vatrano, ... arXiv preprint arXiv:2405.15127, 2024 | | 2024 |