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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
332022
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
122021
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
62023
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
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
12024
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
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
From Normal to Abnormal: Transforming Medical Images with Diffusion Models for Dataset Balancing
M Paulikat, L Nauschütte, MS Kalteis, W Aswolinskiy, A Schneider, ...
Medical Imaging with Deep Learning, 2024
2024
Impact of Layer Selection in Histopathology Foundation Models on Downstream Task Performance
W Aswolinskiy, M Paulikat, C Aichmueller
Medical Imaging with Deep Learning, 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
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