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Patrycja Kowalek
Researcher at Wrocław University of Technology
Publications - 7
Citations - 263
Patrycja Kowalek is an academic researcher from Wrocław University of Technology. The author has contributed to research in topics: Anomalous diffusion & Gradient boosting. The author has an hindex of 3, co-authored 5 publications receiving 85 citations.
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Journal ArticleDOI
Classification of diffusion modes in single-particle tracking data: Feature-based versus deep-learning approach.
TL;DR: A deep-learning method known as a convolutional neural network (CNN) is adopted to classify modes of diffusion from given trajectories and it is shown that CNN is usually slightly better than the feature-based methods, but at the cost of much longer processing times.
Journal ArticleDOI
Objective comparison of methods to decode anomalous diffusion.
Gorka Muñoz-Gil,Giovanni Volpe,Miguel Ángel García-March,Erez Aghion,Aykut Argun,Chang Beom Hong,Tom Bland,Stefano Bo,J. Alberto Conejero,Nicolas Firbas,Òscar Garibo i Orts,Alessia Gentili,Zihan Huang,Jae-Hyung Jeon,Hélène Kabbech,Yeongjin Kim,Patrycja Kowalek,Diego Krapf,Hanna Loch-Olszewska,Michael A. Lomholt,Jean-Baptiste Masson,Philipp G. Meyer,Seongyu Park,Borja Requena,Ihor Smal,Taegeun Song,Taegeun Song,Taegeun Song,Janusz Szwabiński,Samudrajit Thapa,Samudrajit Thapa,Hippolyte Verdier,Giorgio Volpe,Artur Widera,Maciej Lewenstein,Ralf Metzler,Carlo Manzo,Carlo Manzo +37 more
TL;DR: The Anomalous Diffusion Challenge (AnDi) as mentioned in this paper was an open competition for the characterization of anomalous diffusion from the measurement of an individual trajectory, which traditionally relies on calculating the trajectory mean squared displacement.
Posted Content
Objective comparison of methods to decode anomalous diffusion
Gorka Muñoz-Gil,Giovanni Volpe,Miguel Ángel García-March,Erez Aghion,Aykut Argun,Chang Beom Hong,Tom Bland,Stefano Bo,J. Alberto Conejero,Nicolas Firbas,Òscar Garibo i Orts,Alessia Gentili,Zihan Huang,Jae-Hyung Jeon,Hélène Kabbech,Yeongjin Kim,Patrycja Kowalek,Diego Krapf,Hanna Loch-Olszewska,Michael A. Lomholt,Jean-Baptiste Masson,Philipp G. Meyer,Seongyu Park,Borja Requena,Ihor Smal,Taegeun Song,Taegeun Song,Taegeun Song,Janusz Szwabiński,Samudrajit Thapa,Samudrajit Thapa,Hippolyte Verdier,Giorgio Volpe,Artur Widera,Maciej Lewenstein,Ralf Metzler,Carlo Manzo,Carlo Manzo +37 more
TL;DR: This paper presents a meta-anatomy of the response of the immune system to chemotherapy, a model derived from the model developed by Carl Friedrich Gauss in 1916.
Journal ArticleDOI
Classification of particle trajectories in living cells: Machine learning versus statistical testing hypothesis for fractional anomalous diffusion.
TL;DR: A new set of features used to transform the raw trajectories data into input vectors required by the classifiers are presented and the resulting models are applied to real data for G protein-coupled receptors and G proteins.
Journal ArticleDOI
Boosting the performance of anomalous diffusion classifiers with the proper choice of features
TL;DR: In this article , a feature-based machine learning method was developed in response to Task 2 of the Anomalous Diffusion Challenge, i.e. the classification of different types of diffusion.