Bastian Rieck
Bastian Rieck
Other namesBastian Alexander Rieck
AIDOS Lab, Institute of AI for Health, Helmholtz Zentrum München
Verified email at - Homepage
Cited by
Cited by
Early prediction of circulatory failure in the intensive care unit using machine learning
SL Hyland, M Faltys, M Hüser, X Lyu, T Gumbsch, C Esteban, C Bock, ...
Nature Medicine 26 (3), 364-373, 2020
Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A …
CR Jutzeler, L Bourguignon, CV Weis, B Tong, C Wong, B Rieck, ...
Travel medicine and infectious disease 37, 101825, 2020
Wasserstein Weisfeiler-Lehman Graph Kernels
M Togninalli, E Ghisu, F Llinares-López, B Rieck, K Borgwardt
Advances in Neural Information Processing Systems 32, 6436--6446, 2019
Topological Autoencoders
M Moor, M Horn, B Rieck, K Borgwardt
International Conference on Machine Learning (ICML), 7045--7054, 2020
Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis
J Born, N Wiedemann, M Cossio, C Buhre, G Brändle, K Leidermann, ...
Applied Sciences 11 (2), 672, 2021
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
B Rieck, M Togninalli, C Bock, M Moor, M Horn, T Gumbsch, K Borgwardt
International Conference on Learning Representations (ICLR), 2019
A Survey of Topological Machine Learning Methods
F Hensel, M Moor, B Rieck
Frontiers in Artificial Intelligence 4, 681108, 2021
Graph Kernels: State-Of-The-Art and Future Challenges
K Borgwardt, E Ghisu, F Llinares-López, L O’Bray, B Rieck
Foundations and Trends in Machine Learning 13 (5-6), 531-712, 2020
Set Functions for Time Series
M Horn, M Moor, C Bock, B Rieck, K Borgwardt
International Conference on Machine Learning, 4353-4363, 2020
Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping
M Moor, M Horn, B Rieck, D Roqueiro, K Borgwardt
Machine Learning for Healthcare 2019, 2019
Early Prediction of Sepsis in the ICU Using Machine Learning: A Systematic Review
M Moor, B Rieck, M Horn, CR Jutzeler, K Borgwardt
Frontiers in Medicine 8, 2021
A Persistent Weisfeiler–Lehman Procedure for Graph Classification
B Rieck, C Bock, K Borgwardt
International Conference on Machine Learning (ICML), 2019
Graph Filtration Learning
CD Hofer, F Graf, B Rieck, M Niethammer, R Kwitt
Proceedings of the 37th International Conference on Machine Learning 119 …, 2020
Persistent Homology for the Evaluation of Dimensionality Reduction Schemes
B Rieck, H Leitte
Computer Graphics Forum 34 (3), 2015
Clique Community Persistence: A Topological Visual Analysis Approach for Complex Networks
B Rieck, U Fugacci, J Lukasczyk, H Leitte
IEEE Transactions on Visualization and Computer Graphics 24 (1), 822-831, 2018
Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning
C Weis, A Cuénod, B Rieck, O Dubuis, S Graf, C Lang, M Oberle, ...
Nature Medicine 28 (1), 164-174, 2022
Weisfeiler and Leman go Machine Learning: The Story so far
C Morris, Y Lipman, H Maron, B Rieck, NM Kriege, M Grohe, M Fey, ...
arXiv preprint arXiv:2112.09992, 2021
Multivariate Data Analysis Using Persistence-Based Filtering and Topological Signatures
B Rieck, H Mara, H Leitte
IEEE Transactions on Visualization and Computer Graphics 18 (12), 2382-2391, 2012
Topological Graph Neural Networks
M Horn, E De Brouwer, M Moor, Y Moreau, B Rieck, K Borgwardt
international Conference on Learning Representations (ICLR), 2022
A sandbox for prediction and integration of DNA, RNA, and proteins in single cells
MD Luecken, DB Burkhardt, R Cannoodt, C Lance, A Agrawal, H Aliee, ...
Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021
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