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Michael T. Schaub
Michael T. Schaub
RWTH Aachen University
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
SC3: consensus clustering of single-cell RNA-Seq data
VY Kiselev, K Kirschner, MT Schaub, T Andrews, A Yiu, T Chandra, ...
Nature Methods 14 (5), 483-486, 2017
9952017
Simplicial closure and higher-order link prediction
AR Benson, R Abebe, MT Schaub, A Jadbabaie, J Kleinberg
Proceedings of the National Academy of Sciences 115 (48), E11221-E11230, 2018
2592018
Markov dynamics as a zooming lens for multiscale community detection: non clique-like communities and the field-of-view limit
MT Schaub, JC Delvenne, SN Yaliraki, M Barahona
PloS one 7 (2), e32210, 2012
1892012
The many facets of community detection in complex networks
MT Schaub, JC Delvenne, M Rosvall, R Lambiotte
Applied Network Science 2 (1), 4, 2017
1412017
Graph partitions and cluster synchronization in networks of oscillators
MT Schaub, N O'Clery, YN Billeh, JC Delvenne, R Lambiotte, M Barahona
Chaos: An Interdisciplinary Journal of Nonlinear Science 26 (9), 094821, 2016
1282016
Random walks on simplicial complexes and the normalized Hodge 1-Laplacian
MT Schaub, AR Benson, P Horn, G Lippner, A Jadbabaie
SIAM Review 62 (2), 353-391, 2020
1252020
The stability of a graph partition: A dynamics-based framework for community detection
JC Delvenne, MT Schaub, SN Yaliraki, M Barahona
Dynamics On and Of Complex Networks, Volume 2, 221-242, 2013
96*2013
Encoding dynamics for multiscale community detection: Markov time sweeping for the map equation
MT Schaub, R Lambiotte, M Barahona
Physical Review E 86 (2), 026112, 2012
702012
Prediction of allosteric sites and mediating interactions through bond-to-bond propensities
BRC Amor, MT Schaub, SN Yaliraki, M Barahona
Nature Communications 7 (12477), 2016
692016
Centrality measures for graphons: Accounting for uncertainty in networks
M Avella-Medina, F Parise, M Schaub, S Segarra
IEEE Transactions on Network Science and Engineering, 2018
612018
Using higher-order Markov models to reveal flow-based communities in networks
V Salnikov, MT Schaub, R Lambiotte
Scientific reports 6 (1), 1-13, 2016
562016
Flow smoothing and denoising: Graph signal processing in the edge-space
MT Schaub, S Segarra
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018
472018
Emergence of Slow-Switching Assemblies in Structured Neuronal Networks
MT Schaub, YN Billeh, CA Anastassiou, C Koch, M Barahona
PLoS Computational Biology 11 (7), e1004196, 2015
472015
Structure of complex networks: Quantifying edge-to-edge relations by failure-induced flow redistribution
MT Schaub, J Lehmann, SN Yaliraki, M Barahona
Network Science 2 (1), 66-89, 2014
452014
Signal processing on higher-order networks: Livin’on the edge... and beyond
MT Schaub, Y Zhu, JB Seby, TM Roddenberry, S Segarra
Signal Processing 187, 108149, 2021
432021
Multiscale dynamical embeddings of complex networks
MT Schaub, JC Delvenne, R Lambiotte, M Barahona
Physical Review E 99 (6), 062308, 2019
422019
Flow-based network analysis of the Caenorhabditis elegans connectome
KA Bacik, MT Schaub, M Beguerisse-Díaz, YN Billeh, M Barahona
PLoS Comput Biol 12 (8), e1005055, 2016
422016
What are higher-order networks?
C Bick, E Gross, HA Harrington, MT Schaub
arXiv preprint arXiv:2104.11329, 2021
412021
Graph-based semi-supervised & active learning for edge flows
J Jia, MT Schaub, S Segarra, AR Benson
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
412019
The Ising decoder: reading out the activity of large neural ensembles
MT Schaub, SR Schultz
Journal of computational neuroscience 32 (1), 101-118, 2012
412012
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Articles 1–20