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Witali Aswolinskiy
Witali Aswolinskiy
Deep learning & Computational Pathology, Paicon GmbH
Verified email at paicon.com
Title
Cited by
Cited by
Year
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
302022
Time series classification in reservoir-and model-space
W Aswolinskiy, RF Reinhart, J Steil
Neural Processing Letters 48 (2), 789-809, 2018
282018
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
252016
RM-SORN: a reward-modulated self-organizing recurrent neural network
W Aswolinskiy, G Pipa
Frontiers in computational neuroscience 9, 36, 2015
232015
Impact of Regularization on the Model Space for Time Series Classification
W Aswolinskiy, RF Reinhart, J Steil
Workshop New Challenges in Neural Computation, 2015
162015
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
102021
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
92017
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
92016
Modelling of parametrized processes via regression in the model space of neural networks
W Aswolinskiy, RF Reinhart, JJ Steil
Neurocomputing 268, 55-63, 2017
72017
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
42023
Maschinelles lernen in technischen systemen
F Reinhart, K Neumann, W Aswolinskiy, J Steil, B Hammer
Steigerung der Intelligenz mechatronischer Systeme, 73-118, 2018
42018
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
22023
Learning in the model space of neural networks
W Aswolinskiy
22018
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
12023
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
12016
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
2024
Basal cell carcinoma detection using weakly supervised deep learning methods and rule-based labels
D Geijs, S Dooper, W Aswolinskiy, L van Eekelen, A Amir, G Litjens
2022
Potential of an AI-based digital biomarker to predict neoadjuvant chemotherapy response from preoperative biopsies of Luminal-B breast cancer
W Aswolinskiy, H Horlings, L Mulder, J Van der Laak, J Wesseling, E Lips, ...
VIRCHOWS ARCHIV 479, S179-S179, 2021
2021
Berücksichtigung zeitlicher Anforderungen bei der Generierung von Testfällen für den Integrationstest
W Aswolinskiy, Y Lei, M Heidrich
Geselllschaft für Informatik eV, 2008
2008
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Articles 1–19