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ORCIDRicards Marcinkevics
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2020 – today
- 2024
[j2]Ricards Marcinkevics
, Patricia Reis Wolfertstetter, Ugne Klimiene, Kieran Chin-Cheong, Alyssia Paschke, Julia Zerres, Markus Denzinger, David Niederberger, Sven Wellmann, Ece Ozkan, Christian Knorr, Julia E. Vogt:
Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis. Medical Image Anal. 91: 103042 (2024)- [i10]Ricards Marcinkevics, Sonia Laguna, Moritz Vandenhirtz, Julia E. Vogt:
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable? CoRR abs/2401.13544 (2024) - [i9]Moritz Vandenhirtz, Sonia Laguna, Ricards Marcinkevics, Julia E. Vogt:
Stochastic Concept Bottleneck Models. CoRR abs/2406.19272 (2024) - 2023
- [j1]Ricards Marcinkevics, Julia E. Vogt:
Interpretable and explainable machine learning: A methods-centric overview with concrete examples. WIREs Data. Mining. Knowl. Discov. 13(3) (2023) - [c7]Zixuan Xiao, Michal Muszynski, Ricards Marcinkevics, Lukas Zimmerli, Adam Daniel Ivankay, Dario Kohlbrenner, Manuel Kuhn, Yves Nordmann, Ulrich Muehlner, Christian F. Clarenbach, Julia E. Vogt, Thomas Brunschwiler:
Breathing New Life into COPD Assessment: Multisensory Home-monitoring for Predicting Severity. ICMI 2023: 84-93 - [i8]Ricards Marcinkevics, Patricia Reis Wolfertstetter, Ugne Klimiene, Ece Ozkan, Kieran Chin-Cheong, Alyssia Paschke, Julia Zerres, Markus Denzinger, David Niederberger, Sven Wellmann, Christian Knorr, Julia E. Vogt:
Interpretable and Intervenable Ultrasonography-based Machine Learning Models for Pediatric Appendicitis. CoRR abs/2302.14460 (2023) - [i7]Moritz Vandenhirtz, Laura Manduchi, Ricards Marcinkevics, Julia E. Vogt:
Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss. CoRR abs/2305.19671 (2023) - 2022
- [c6]Laura Manduchi, Ricards Marcinkevics, Michela Carlotta Massi, Thomas J. Weikert, Alexander Sauter, Verena Gotta, Timothy Müller, Flavio Vasella, Marian C. Neidert, Marc Pfister, Bram Stieltjes, Julia E. Vogt:
A Deep Variational Approach to Clustering Survival Data. ICLR 2022 - [c5]Ricards Marcinkevics, Ece Ozkan, Julia E. Vogt:
Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods. MLHC 2022: 504-536 - [i6]Ricards Marcinkevics, Ece Ozkan, Julia E. Vogt:
Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods. CoRR abs/2208.00781 (2022) - [i5]Ricards Marcinkevics, Ece Ozkan, Julia E. Vogt:
Introduction to Machine Learning for Physicians: A Survival Guide for Data Deluge. CoRR abs/2212.12303 (2022) - 2021
- [c4]Alexander H. Hatteland, Ricards Marcinkevics, Renaud Marquis, Thomas Frick, Ilona Hubbard, Julia E. Vogt, Thomas Brunschwiler, Philippe Ryvlin:
Exploring Relationships between Cerebral and Peripheral Biosignals with Neural Networks. ICDH 2021: 103-113 - [c3]Ricards Marcinkevics, Julia E. Vogt:
Interpretable Models for Granger Causality Using Self-explaining Neural Networks. ICLR 2021 - [c2]Pedro Roig Aparicio, Ricards Marcinkevics, Patricia Reis Wolfertstetter, Sven Wellmann, Christian Knorr, Julia E. Vogt:
Learning Medical Risk Scores for Pediatric Appendicitis. ICMLA 2021: 1507-1512 - [i4]Ricards Marcinkevics, Julia E. Vogt:
Interpretable Models for Granger Causality Using Self-explaining Neural Networks. CoRR abs/2101.07600 (2021) - [i3]Laura Manduchi, Ricards Marcinkevics, Michela Carlotta Massi, Verena Gotta, Timothy Müller, Flavio Vasella, Marian C. Neidert, Marc Pfister, Julia E. Vogt:
A Deep Variational Approach to Clustering Survival Data. CoRR abs/2106.05763 (2021) - 2020
- [c1]Imant Daunhawer, Thomas M. Sutter, Ricards Marcinkevics, Julia E. Vogt:
Self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models. GCPR 2020: 459-473 - [i2]Ricards Marcinkevics, Julia E. Vogt:
Interpretability and Explainability: A Machine Learning Zoo Mini-tour. CoRR abs/2012.01805 (2020)
2010 – 2019
- 2019
- [i1]Ricards Marcinkevics, Steven Kelk, Carlo Galuzzi, Berthold Stegemann:
Discovery of Important Subsequences in Electrocardiogram Beats Using the Nearest Neighbour Algorithm. CoRR abs/1901.09187 (2019)
Coauthor Index
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