Spremljaj
Bastian Rieck
Bastian Rieck
Druga imenaBastian Alexander Rieck, Bastian Grossenbacher-Rieck
Professor, AIDOS Lab, University of Fribourg
Preverjeni e-poštni naslov na unifr.ch - Domača stran
Naslov
Navedeno
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Leto
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
3772020
Wasserstein Weisfeiler-Lehman Graph Kernels
M Togninalli, E Ghisu, F Llinares-López, B Rieck, K Borgwardt
Advances in Neural Information Processing Systems (NeurIPS) 32, 6436--6446, 2019
2672019
A Survey of Topological Machine Learning Methods
F Hensel, M Moor, B Rieck
Frontiers in Artificial Intelligence 4, 681108, 2021
2242021
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
2242020
Topological Autoencoders
M Moor, M Horn, B Rieck, K Borgwardt
International Conference on Machine Learning, 7045--7054, 2020
2012020
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
1642021
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
1512019
Set Functions for Time Series
M Horn, M Moor, C Bock, B Rieck, K Borgwardt
International Conference on Machine Learning (ICML), 4353-4363, 2020
1492020
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
1452021
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
1362022
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
1362020
Weisfeiler and Leman go Machine Learning: The Story so far
C Morris, Y Lipman, H Maron, B Rieck, NM Kriege, M Grohe, M Fey, ...
Journal of Machine Learning Research 24 (333), 1--59, 2023
1312023
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
114*2019
Graph Filtration Learning
CD Hofer, F Graf, B Rieck, M Niethammer, R Kwitt
International Conference on Machine Learning (ICML) 119, 4314--4323, 2020
1122020
A Persistent Weisfeiler–Lehman Procedure for Graph Classification
B Rieck, C Bock, K Borgwardt
International Conference on Machine Learning (ICML), 2019
1072019
Topological Graph Neural Networks
M Horn, E De Brouwer, M Moor, Y Moreau, B Rieck, K Borgwardt
international Conference on Learning Representations (ICLR), 2022
1062022
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, ...
Advances in Neural Information Processing Systems (NeurIPS Datasets and …, 2021
962021
Persistent Homology for the Evaluation of Dimensionality Reduction Schemes
B Rieck, H Leitte
Computer Graphics Forum 34 (3), 2015
802015
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
732018
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence
B Rieck, T Yates, C Bock, K Borgwardt, G Wolf, N Turk-Browne†, ...
Advances in Neural Information Processing Systems (NeurIPS) 33, 2020
672020
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