| Interpretability and explainability: A machine learning zoo mini-tour R Marcinkevičs, JE Vogt arXiv preprint arXiv:2012.01805, 2020 | 170 | 2020 |
| Interpretable models for Granger causality using self-explaining neural networks R Marcinkevičs, JE Vogt The 9th International Conference on Learning Representations, ICLR 2021, 2021 | 55 | 2021 |
| Using machine learning to predict the diagnosis, management and severity of pediatric appendicitis R Marcinkevics, P Reis Wolfertstetter, S Wellmann, C Knorr, JE Vogt Frontiers in pediatrics 9, 662183, 2021 | 41 | 2021 |
| Interpretable and explainable machine learning: A methods‐centric overview with concrete examples R Marcinkevičs, JE Vogt Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13 (3 …, 2023 | 38 | 2023 |
| A Deep Variational Approach to Clustering Survival Data L Manduchi, R Marcinkevičs, MC Massi, T Weikert, A Sauter, V Gotta, ... The 10th International Conference on Learning Representations, ICLR 2022, 2022 | 36 | 2022 |
| Rapid and reversible control of human metabolism by individual sleep states N Nowak, T Gaisl, D Miladinovic, R Marcinkevics, M Osswald, S Bauer, ... Cell Reports 37 (4), 2021 | 32 | 2021 |
| Self-supervised disentanglement of modality-specific and shared factors improves multimodal generative models I Daunhawer, TM Sutter, R Marcinkevičs, JE Vogt Pattern Recognition: 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen …, 2021 | 26 | 2021 |
| Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis R Marcinkevičs, PR Wolfertstetter, U Klimiene, K Chin-Cheong, ... Medical Image Analysis, 103042, 2023 | 20* | 2023 |
| Debiasing deep chest X-ray classifiers using intra-and post-processing methods R Marcinkevics, E Ozkan, JE Vogt Machine Learning for Healthcare Conference, 504-536, 2022 | 20 | 2022 |
| Multichannel electrocardiogram diagnostics for the diagnosis of arrhythmogenic right ventricular dysplasia R Marcinkevics, J O’neill, H Law, E Pervolaraki, A Hogarth, C Russell, ... EP Europace 20 (FI1), f13-f19, 2018 | 8 | 2018 |
| Learning medical risk scores for pediatric appendicitis PR Aparicio, R Marcinkevičs, PR Wolfertstetter, S Wellmann, C Knorr, ... 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 7 | 2021 |
| Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable? R Marcinkevičs, S Laguna, M Vandenhirtz, J Vogt XAI in Action: Past, Present, and Future Applications, 2023 | 4 | 2023 |
| Introduction to Machine Learning for Physicians: A Survival Guide for Data Deluge JE Vogt, E Özkan Elsen, R Marcinkevičs Digital Medicine: Bringing Digital Solutions to Medical Practice, 2023 | 2* | 2023 |
| Machine learning analysis of humoral and cellular responses to SARS-CoV-2 infection in young adults R Marcinkevics, PN Silva, AK Hankele, C Dörnte, S Kadelka, K Csik, ... Frontiers in Immunology 14, 2608, 2023 | 1 | 2023 |
| Stochastic Concept Bottleneck Models M Vandenhirtz, S Laguna, R Marcinkevičs, JE Vogt arXiv preprint arXiv:2406.19272, 2024 | | 2024 |
| Breathing New Life into COPD Assessment: Multisensory Home-monitoring for Predicting Severity Z Xiao, M Muszynski, R Marcinkevičs, L Zimmerli, AD Ivankay, ... Proceedings of the 25th International Conference on Multimodal Interaction …, 2023 | | 2023 |
| Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss M Vandenhirtz, L Manduchi, R Marcinkevičs, JE Vogt What do we need for successful domain generalization? ICLR 2023, 2023 | | 2023 |
| Multimodal Remote Home Monitoring of Lung Transplant Recipients during COVID-19 Vaccinations: Usability Pilot Study of the COVIDA Desk Incorporating Wearable Devices MM Schuurmans, M Muszynski, X Li, R Marcinkevičs, L Zimmerli, ... Medicina 59 (3), 617, 2023 | | 2023 |
| Exploring Relationships between Cerebral and Peripheral Biosignals with Neural Networks AH Hatteland, R Marcinkevičs, R Marquis, T Frick, I Hubbard, JE Vogt, ... 2021 IEEE International Conference on Digital Health (ICDH), 103-113, 2021 | | 2021 |
| Causal Inference in Time Series for Identifying Molecular Fingerprints during Sleep R Marcinkevics ETH Zürich, 2019 | | 2019 |
Julia E VogtETH Zurich在 inf.ethz.ch 的电子邮件经过验证
