Bastian Rieck

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Karsten BorgwardtDirector, Max Planck Institute of BiochemistryPatvirtintas el. paštas biochem.mpg.de
Michael MoorMD, PhD. Assistant Professor at ETH Zurich. Previously: Stanford, Computer Science.Patvirtintas el. paštas bsse.ethz.ch
Max HornApplied Scientist in Causal Representation Learning, Amazon AWS AIPatvirtintas el. paštas amazon.de
Christian BockAWS AIPatvirtintas el. paštas amazon.de
Heike LeitteProfessor of Computer Science, TU KaiserslauternPatvirtintas el. paštas cs.uni-kl.de
Smita KrishnaswamyYale UniversityPatvirtintas el. paštas yale.edu
Guy WolfUniversité de Montréal; MilaPatvirtintas el. paštas umontreal.ca
Caroline WeisSenior AI/ML Engineer, Team Lead Clinical AI GSK.ai | PhD Machine Learning for Healthcare ETHPatvirtintas el. paštas bsse.ethz.ch
Adrian EgliUniversity of ZurichPatvirtintas el. paštas imm.uzh.ch
Catherine Jutzeler, PhDBiomedical Data Science Lab, D-HEST, ETH ZürichPatvirtintas el. paštas hest.ethz.ch
Filip SadloHeidelberg University, GermanyPatvirtintas el. paštas iwr.uni-heidelberg.de
Matteo TogninalliCo-founder of Visium; PhD from ETH ZurichPatvirtintas el. paštas bsse.ethz.ch
Jannis BornIBM Research EuropePatvirtintas el. paštas zurich.ibm.com
Elisabetta GhisuPhD student, ETH ZurichPatvirtintas el. paštas bsse.ethz.ch
Felipe Llinares-LópezCo-founder and Principal Research Scientist at BioptimusPatvirtintas el. paštas bioptimus.com
Aline CuénodPostdoc at McGill University, Montréal, CanadaPatvirtintas el. paštas mail.mcgill.ca
Roland KwittProfessor, Department of Artificial Intelligence and Human Interfaces, University of SalzburgPatvirtintas el. paštas plus.ac.at
Manuel CossioUniversitat de BarcelonaPatvirtintas el. paštas ub.edu
Dhananjay BhaskarPostdoctoral Associate, Yale UniversityPatvirtintas el. paštas yale.edu
Felix HenselETH ZurichPatvirtintas el. paštas bsse.ethz.ch

Stebėti

Bastian Rieck

Kiti vardaiBastian Alexander Rieck, Bastian Grossenbacher-Rieck

Professor, AIDOS Lab, University of Fribourg

Patvirtintas el. paštas unifr.ch - Pagrindinis puslapis

Geometric Deep Learning Topological Data Analysis Topological Deep Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	411	2020
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	284	2019
A Survey of Topological Machine Learning Methods F Hensel, M Moor, B Rieck Frontiers in Artificial Intelligence 4, 681108, 2021	252	2021
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	229	2020
Topological Autoencoders M Moor, M Horn, B Rieck, K Borgwardt International Conference on Machine Learning, 7045--7054, 2020	221	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	172	2021
Set Functions for Time Series M Horn, M Moor, C Bock, B Rieck, K Borgwardt International Conference on Machine Learning (ICML), 4353-4363, 2020	165	2020
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	159	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	159	2019
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	155	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, ... Journal of Machine Learning Research 24 (333), 1--59, 2023	147	2023
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	142	2020
Topological Graph Neural Networks M Horn, E De Brouwer, M Moor, Y Moreau, B Rieck, K Borgwardt international Conference on Learning Representations (ICLR), 2022	131	2022
Graph Filtration Learning CD Hofer, F Graf, B Rieck, M Niethammer, R Kwitt International Conference on Machine Learning (ICML) 119, 4314--4323, 2020	124	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	120*	2019
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	114	2021
A Persistent Weisfeiler–Lehman Procedure for Graph Classification B Rieck, C Bock, K Borgwardt International Conference on Machine Learning (ICML), 2019	114	2019
Persistent Homology for the Evaluation of Dimensionality Reduction Schemes B Rieck, H Leitte Computer Graphics Forum 34 (3), 2015	86	2015
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	80	2020
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	72	2018

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