Ricards Marcinkevics

发表

Self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models

Julia E. Vogt, Thomas M. Sutter, Imant Daunhawer, 2021, GCPR.

Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods

Julia E. Vogt, Ece Ozkan, Ricards Marcinkevics, 2022, MLHC.

Learning Medical Risk Scores for Pediatric Appendicitis

Julia E. Vogt, S. Wellmann, C. Knorr, 2021, 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).

Multiview Concept Bottleneck Models Applied to Diagnosing Pediatric Appendicitis

Julia E. Vogt, Ece Ozkan, S. Wellmann, 2022 .

Introduction to Machine Learning for Physicians: A Survival Guide for Data Deluge

Julia E. Vogt, Ece Ozkan, Ricards Marcinkevics, 2022, ArXiv.

Interpretable Models for Granger Causality Using Self-explaining Neural Networks pdf

Julia E. Vogt, Ricards Marcinkevics, Ricards Marcinkevics, 2021, ICLR.

Interpretability and Explainability: A Machine Learning Zoo Mini-tour pdf

Julia E. Vogt, Ricards Marcinkevics, Ricards Marcinkevics, 2020, ArXiv.

Interpretability and Explainability: A Machine Learning Zoo Mini-tour

Julia E. Vogt, Ricards Marcinkevics, 2020, ArXiv.

Rapid and reversible control of human metabolism by individual sleep states.

Steven A. Brown, J. Buhmann, R. Zenobi, 2021, Cell reports.

Interpretable and explainable machine learning: A methods‐centric overview with concrete examples

Julia E. Vogt, Ricards Marcinkevics, 2023, WIREs Data. Mining. Knowl. Discov..

Using Machine Learning to Predict the Diagnosis, Management and Severity of Pediatric Appendicitis

Julia E. Vogt, S. Wellmann, C. Knorr, 2021, Frontiers in Pediatrics.

A Deep Variational Approach to Clustering Survival Data

Julia E. Vogt, V. Gotta, M. Pfister, 2021, ICLR.

Machine learning analysis of humoral and cellular responses to SARS-CoV-2 infection in young adults

Julia E. Vogt, J. Goldhahn, M. Stoffel, 2023, Frontiers in Immunology.

Interpretable and Intervenable Ultrasonography-based Machine Learning Models for Pediatric Appendicitis

Julia E. Vogt, Markus Denzinger, Ece Ozkan, 2023, Medical Image Anal..

Multimodal Remote Home Monitoring of Lung Transplant Recipients during COVID-19 Vaccinations: Usability Pilot Study of the COVIDA Desk Incorporating Wearable Devices

Julia E. Vogt, L. Zimmerli, T. Brunschwiler, 2023, Medicina.

Multichannel electrocardiogram diagnostics for the diagnosis of arrhythmogenic right ventricular dysplasia.

A. Holden, E. Pervolaraki, B. Stegemann, 2018, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss

Julia E. Vogt, L. Manduchi, Ricards Marcinkevics, 2023, ArXiv.

Stochastic Concept Bottleneck Models

Ricards Marcinkevics, Moritz Vandenhirtz, Julia E. Vogt, 2024, ArXiv.

Exploring Relationships between Cerebral and Peripheral Biosignals with Neural Networks

Thomas Brunschwiler, Julia E. Vogt, Philippe Ryvlin, 2021, 2021 IEEE International Conference on Digital Health (ICDH).