Bastian Rieck

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Citations	2421	2334
h-index	25	24
i10-index	37	36

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Karsten BorgwardtDirector, Max Planck Institute of BiochemistryVerified email at biochem.mpg.de
Michael MoorMD, PhD. Postdoctoral researcher at Stanford University, Department of Computer Science.Verified email at stanford.edu
Max HornApplied Scientist in Causal Representation Learning, Amazon AWS AIVerified email at amazon.de
Christian BockAWS AIVerified email at amazon.de
Heike LeitteProfessor of Computer Science, TU KaiserslauternVerified email at cs.uni-kl.de
Smita KrishnaswamyYale UniversityVerified email at yale.edu
Caroline WeisAI/ML Engineer for Biomedical AI at GSK.ai | PhD Machine Learning for Healthcare ETH ZurichVerified email at bsse.ethz.ch
Catherine Jutzeler, PhDBiomedical Data Science Lab, D-HEST, ETH ZürichVerified email at hest.ethz.ch
Adrian EgliUniversity of ZurichVerified email at imm.uzh.ch
Leslie O'BrayPhD Student, Machine Learning and Computational Biology, ETH ZürichVerified email at bsse.ethz.ch
Filip SadloHeidelberg University, GermanyVerified email at iwr.uni-heidelberg.de
Guy WolfUniversité de Montréal; MilaVerified email at umontreal.ca
Jannis BornIBM Research EuropeVerified email at zurich.ibm.com
Matteo TogninalliCOO @Visium; PhD from ETH ZurichVerified email at bsse.ethz.ch
Elisabetta GhisuPhD student, ETH ZurichVerified email at bsse.ethz.ch
Felipe Llinares-LópezGoogle DeepMindVerified email at google.com
avinash aujayebConsultant in acute and respiratory medicineVerified email at nhct.nhs.uk
Manuel CossioUniversitat de BarcelonaVerified email at ub.edu
Nina WiedemannETH ZürichVerified email at ethz.ch
Cristóbal EstebanCambrian Intelligence SLU; ETH ZurichVerified email at ethz.ch

Bastian Rieck

Other namesBastian Alexander Rieck

AIDOS Lab, Institute of AI for Health, Helmholtz Zentrum München

Verified email at helmholtz-muenchen.de - Homepage

Topological Machine Learning Topological Data Analysis Geometric Deep Learning Biomedicine


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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	228	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	196	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	180	2019
Topological Autoencoders M Moor, M Horn, B Rieck, K Borgwardt International Conference on Machine Learning (ICML), 7045--7054, 2020	125	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	118	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	113	2019
A Survey of Topological Machine Learning Methods F Hensel, M Moor, B Rieck Frontiers in Artificial Intelligence 4, 681108, 2021	100	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	92	2020
Set Functions for Time Series M Horn, M Moor, C Bock, B Rieck, K Borgwardt International Conference on Machine Learning, 4353-4363, 2020	87	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	85*	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	82	2021
A Persistent Weisfeiler–Lehman Procedure for Graph Classification B Rieck, C Bock, K Borgwardt International Conference on Machine Learning (ICML), 2019	79	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	71	2020
Persistent Homology for the Evaluation of Dimensionality Reduction Schemes B Rieck, H Leitte Computer Graphics Forum 34 (3), 2015	71	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	57	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	53	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	53	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	50	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	42	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	39	2021

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