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ORCIDMichael T. Schaub
Person information
- affiliation: Université catholique de Louvain, Louvain-la-Neuve, Belgium
- affiliation: SocietyMassachusetts Institute of Technology, Cambridge, MA, USA
- affiliation: University of Oxford, UK
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2020 – today
- 2023
[j21]Christian Bick
, Elizabeth Gross, Heather A. Harrington, Michael T. Schaub:
What Are Higher-Order Networks? SIAM Rev. 65(3): 686-731 (2023)- [c14]Vincent Peter Grande, Michael T. Schaub:
Topological Point Cloud Clustering. ICML 2023: 11683-11697 - [c13]Felix I. Stamm, Michael Scholkemper, Michael T. Schaub, Markus Strohmaier:
Neighborhood Structure Configuration Models. WWW 2023: 210-220 - [i52]Lucille Calmon, Michael T. Schaub, Ginestra Bianconi:
Dirac signal processing of higher-order topological signals. CoRR abs/2301.10137 (2023) - [i51]Alexis Arnaudon, Dominik J. Schindler, Robert L. Peach, Adam Gosztolai, Maxwell Hodges, Michael T. Schaub, Mauricio Barahona:
PyGenStability: Multiscale community detection with generalized Markov Stability. CoRR abs/2303.05385 (2023) - [i50]Vincent P. Grande, Michael T. Schaub:
Topological Point Cloud Clustering. CoRR abs/2303.16716 (2023) - [i49]Michael Scholkemper, Michael T. Schaub:
An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions. CoRR abs/2305.19087 (2023) - [i48]Leonie Neuhäuser, Michael Scholkemper, Francesco Tudisco, Michael T. Schaub:
Learning the effective order of a hypergraph dynamical system. CoRR abs/2306.01813 (2023) - [i47]Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra:
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks. CoRR abs/2306.05557 (2023) - [i46]Josef Hoppe, Michael T. Schaub:
Representing Edge Flows on Graphs via Sparse Cell Complexes. CoRR abs/2309.01632 (2023) - [i45]James Shiniti Nagai, Ivan G. Costa, Michael T. Schaub:
Optimal transport distances for directed, weighted graphs: a case study with cell-cell communication networks. CoRR abs/2309.07030 (2023) - 2022
- [j20]Florian Klimm, Nick S. Jones, Michael T. Schaub:
Modularity Maximization for Graphons. SIAM J. Appl. Math. 82(6): 1930-1952 (2022) - [j19]Maosheng Yang, Elvin Isufi, Michael T. Schaub, Geert Leus:
Simplicial Convolutional Filters. IEEE Trans. Signal Process. 70: 4633-4648 (2022) - [c12]Lucille Calmon, Michael T. Schaub, Ginestra Bianconi:
Higher-order signal processing with the Dirac operator. IEEECONF 2022: 925-929 - [c11]Michael Scholkemper, Michael T. Schaub:
Blind Extraction of Equitable Partitions from Graph Signals. ICASSP 2022: 5832-5836 - [c10]T. Mitchell Roddenberry, Florian Frantzen, Michael T. Schaub, Santiago Segarra:
Hodgelets: Localized Spectral Representations of Flows On Simplicial Complexes. ICASSP 2022: 5922-5926 - [c9]T. Mitchell Roddenberry, Michael T. Schaub, Mustafa Hajij:
Signal Processing On Cell Complexes. ICASSP 2022: 8852-8856 - [c8]Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra:
How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications. KDD 2022: 2637-2647 - [i44]Maosheng Yang, Elvin Isufi, Michael T. Schaub, Geert Leus:
Simplicial Convolutional Filters. CoRR abs/2201.11720 (2022) - [i43]Michael Scholkemper, Michael T. Schaub:
Blind Extraction of Equitable Partitions from Graph Signals. CoRR abs/2203.05407 (2022) - [i42]Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra:
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods. CoRR abs/2207.04376 (2022) - [i41]Leonie Neuhäuser, Fariba Karimi, Jan Bachmann, Markus Strohmaier, Michael T. Schaub:
Improving the visibility of minorities through network growth interventions. CoRR abs/2208.03263 (2022) - [i40]Felix I. Stamm, Michael Scholkemper, Markus Strohmaier, Michael T. Schaub:
Neighborhood Structure Configuration Models. CoRR abs/2210.06843 (2022) - [i39]Lucille Calmon, Michael T. Schaub, Ginestra Bianconi:
Higher-order signal processing with the Dirac operator. CoRR abs/2212.10196 (2022) - 2021
- [j18]Leonie Neuhäuser, Felix I. Stamm, Florian Lemmerich, Michael T. Schaub, Markus Strohmaier:
Simulating systematic bias in attributed social networks and its effect on rankings of minority nodes. Appl. Netw. Sci. 6(1): 86 (2021) - [j17]James Shiniti Nagai, Nils B. Leimkühler, Michael T. Schaub, Rebekka K. Schneider, Ivan G. Costa:
CrossTalkeR: analysis and visualization of ligand-receptorne tworks. Bioinform. 37(22): 4263-4265 (2021) - [j16]Michael T. Schaub, Yu Zhu, Jean-Baptiste Seby, T. Mitchell Roddenberry, Santiago Segarra:
Signal processing on higher-order networks: Livin' on the edge... and beyond. Signal Process. 187: 108149 (2021) - [c7]Florian Frantzen, Jean-Baptiste Seby, Michael T. Schaub:
Outlier Detection for Trajectories via Flow-embeddings. ACSCC 2021: 1568-1572 - [c6]Maosheng Yang, Elvin Isufi, Michael T. Schaub, Geert Leus:
Finite Impulse Response Filters for Simplicial Complexes. EUSIPCO 2021: 2005-2009 - [i38]Florian Klimm, Nick S. Jones, Michael T. Schaub:
Modularity maximisation for graphons. CoRR abs/2101.00503 (2021) - [i37]Michael T. Schaub, Yu Zhu, Jean-Baptiste Seby, T. Mitchell Roddenberry, Santiago Segarra:
Signal Processing on Higher-Order Networks: Livin' on the Edge ... and Beyond. CoRR abs/2101.05510 (2021) - [i36]Maosheng Yang, Elvin Isufi, Michael T. Schaub, Geert Leus:
Finite Impulse Response Filters for Simplicial Complexes. CoRR abs/2103.12587 (2021) - [i35]Christian Bick, Elizabeth Gross, Heather A. Harrington, Michael T. Schaub:
What are higher-order networks? CoRR abs/2104.11329 (2021) - [i34]Leonie Neuhäuser, Renaud Lambiotte, Michael T. Schaub:
Consensus Dynamics and Opinion Formation on Hypergraphs. CoRR abs/2105.01369 (2021) - [i33]Michael Scholkemper, Michael T. Schaub:
Local, global and scale-dependent node roles. CoRR abs/2105.12598 (2021) - [i32]Michael T. Schaub, Jean-Baptiste Seby, Florian Frantzen, T. Mitchell Roddenberry, Yu Zhu, Santiago Segarra:
Signal processing on simplicial complexes. CoRR abs/2106.07471 (2021) - [i31]Jiong Zhu, Junchen Jin, Michael T. Schaub, Danai Koutra:
Improving Robustness of Graph Neural Networks with Heterophily-Inspired Designs. CoRR abs/2106.07767 (2021) - [i30]Leonie Neuhäuser, Renaud Lambiotte, Michael T. Schaub:
Consensus dynamics on temporal hypergraphs. CoRR abs/2109.04985 (2021) - [i29]T. Mitchell Roddenberry, Florian Frantzen, Michael T. Schaub, Santiago Segarra:
Hodgelets: Localized Spectral Representations of Flows on Simplicial Complexes. CoRR abs/2109.08728 (2021) - [i28]T. Mitchell Roddenberry, Michael T. Schaub, Mustafa Hajij:
Signal Processing on Cell Complexes. CoRR abs/2110.05614 (2021) - [i27]Florian Frantzen, Jean-Baptiste Seby, Michael T. Schaub:
Outlier Detection for Trajectories via Flow-embeddings. CoRR abs/2111.13235 (2021) - 2020
- [j15]Michael T. Schaub, Austin R. Benson, Paul Horn, Gabor Lippner, Ali Jadbabaie:
Random Walks on Simplicial Complexes and the Normalized Hodge 1-Laplacian. SIAM Rev. 62(2): 353-391 (2020) - [j14]Michael T. Schaub, Santiago Segarra, John N. Tsitsiklis:
Blind Identification of Stochastic Block Models from Dynamical Observations. SIAM J. Math. Data Sci. 2(2): 335-367 (2020) - [j13]Marco Avella-Medina, Francesca Parise, Michael T. Schaub, Santiago Segarra:
Centrality Measures for Graphons: Accounting for Uncertainty in Networks. IEEE Trans. Netw. Sci. Eng. 7(1): 520-537 (2020) - [j12]Yu Zhu, Michael T. Schaub, Ali Jadbabaie, Santiago Segarra:
Network Inference From Consensus Dynamics With Unknown Parameters. IEEE Trans. Signal Inf. Process. over Networks 6: 300-315 (2020) - [j11]T. Mitchell Roddenberry, Michael T. Schaub, Hoi-To Wai, Santiago Segarra:
Exact Blind Community Detection From Signals on Multiple Graphs. IEEE Trans. Signal Process. 68: 5016-5030 (2020) - [c5]Leonie Neuhäuser, Michael T. Schaub, Andrew Mellor, Renaud Lambiotte:
Opinion Dynamics with Multi-body Interactions. NetGCooP 2020: 261-271 - [i26]T. Mitchell Roddenberry, Michael T. Schaub, Hoi-To Wai, Santiago Segarra:
Exact Blind Community Detection from Signals on Multiple Graphs. CoRR abs/2001.10944 (2020) - [i25]Michael T. Schaub, Leto Peel:
Hierarchical community structure in networks. CoRR abs/2009.07196 (2020) - [i24]Leto Peel, Michael T. Schaub:
Detectability of hierarchical communities in networks. CoRR abs/2009.07525 (2020) - [i23]Felix I. Stamm, Leonie Neuhäuser, Florian Lemmerich, Michael T. Schaub, Markus Strohmaier:
Systematic edge uncertainty in attributed social networks and its effects on rankings of minority nodes. CoRR abs/2010.11546 (2020)
2010 – 2019
- 2019
- [c4]Michael T. Schaub, Santiago Segarra, Hoi-To Wai:
Spectral Partitioning of Time-varying Networks with Unobserved Edges. ICASSP 2019: 4938-4942 - [c3]Junteng Jia, Michael T. Schaub, Santiago Segarra, Austin R. Benson:
Graph-based Semi-Supervised & Active Learning for Edge Flows. KDD 2019: 761-771 - [i22]Michael T. Schaub, Santiago Segarra, Hoi-To Wai:
Spectral partitioning of time-varying networks with unobserved edges. CoRR abs/1904.11930 (2019) - [i21]Junteng Jia, Michael T. Schaub, Santiago Segarra, Austin R. Benson:
Graph-based Semi-Supervised & Active Learning for Edge Flows. CoRR abs/1905.07451 (2019) - [i20]Michael T. Schaub, Santiago Segarra, John N. Tsitsiklis:
Blind identification of stochastic block models from dynamical observations. CoRR abs/1905.09107 (2019) - [i19]Yu Zhu, Michael T. Schaub, Ali Jadbabaie, Santiago Segarra:
Network Inference from Consensus Dynamics with Unknown Parameters. CoRR abs/1908.01393 (2019) - 2018
- [j10]Ernesto Estrada, Jean-Charles Delvenne, Naomichi Hatano, José L. Mateos, Ralf Metzler, Alejandro P. Riascos, Michael T. Schaub:
Random multi-hopper model: super-fast random walks on graphs. J. Complex Networks 6(3): 382-403 (2018) - [j9]Mauro Faccin, Michael T. Schaub, Jean-Charles Delvenne:
Entrograms and coarse graining of dynamics on complex networks. J. Complex Networks 6(5): 661-678 (2018) - [j8]Yazan N. Billeh, Michael T. Schaub:
Feedforward architectures driven by inhibitory interactions. J. Comput. Neurosci. 44(1): 63-74 (2018) - [j7]Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, Jon M. Kleinberg:
Simplicial closure and higher-order link prediction. Proc. Natl. Acad. Sci. USA 115(48): E11221-E11230 (2018) - [c2]Michael T. Schaub, Santiago Segarra:
Flow Smoothing and Denoising: Graph Signal Processing in the Edge-Space. GlobalSIP 2018: 735-739 - [i18]Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, Jon M. Kleinberg:
Simplicial Closure and Higher-order Link Prediction. CoRR abs/1802.06916 (2018) - [i17]Michael T. Schaub, Jean-Charles Delvenne, Renaud Lambiotte, Mauricio Barahona:
Multiscale dynamical embeddings of complex networks. CoRR abs/1804.03733 (2018) - [i16]Michael T. Schaub, Jean-Charles Delvenne, Renaud Lambiotte, Mauricio Barahona:
Structured networks and coarse-grained descriptions: a dynamical perspective. CoRR abs/1804.06268 (2018) - [i15]Michael T. Schaub, Austin R. Benson, Paul Horn, Gabor Lippner, Ali Jadbabaie:
Random Walks on Simplicial Complexes and the normalized Hodge Laplacian. CoRR abs/1807.05044 (2018) - [i14]Michael T. Schaub, Santiago Segarra:
Flow Smoothing and Denoising: Graph Signal Processing in the Edge-Space. CoRR abs/1808.02111 (2018) - 2017
- [j6]Michael T. Schaub, Jean-Charles Delvenne, Martin Rosvall, Renaud Lambiotte:
The many facets of community detection in complex networks. Appl. Netw. Sci. 2: 4 (2017) - [j5]Michael T. Schaub, Maguy Trefois, Paul Van Dooren, Jean-Charles Delvenne:
Sparse Matrix Factorizations for Fast Linear Solvers with Application to Laplacian Systems. SIAM J. Matrix Anal. Appl. 38(2): 505-529 (2017) - [c1]Santiago Segarra, Michael T. Schaub, Ali Jadbabaie:
Network inference from consensus dynamics. CDC 2017: 3212-3217 - [i13]Marco Avella-Medina, Francesca Parise, Michael T. Schaub, Santiago Segarra:
Centrality measures for graphons. CoRR abs/1707.09350 (2017) - [i12]Santiago Segarra, Michael T. Schaub, Ali Jadbabaie:
Network Inference from Consensus Dynamics. CoRR abs/1708.05329 (2017) - [i11]Mauro Faccin, Michael T. Schaub, Jean-Charles Delvenne:
Entrograms and coarse graining of dynamics on complex networks. CoRR abs/1711.01987 (2017) - [i10]Martin Rosvall, Jean-Charles Delvenne, Michael T. Schaub, Renaud Lambiotte:
Different approaches to community detection. CoRR abs/1712.06468 (2017) - 2016
- [j4]Karol A. Bacik, Michael T. Schaub, Mariano Beguerisse-Díaz, Yazan N. Billeh, Mauricio Barahona:
Flow-Based Network Analysis of the Caenorhabditis elegans Connectome. PLoS Comput. Biol. 12(8) (2016) - [i9]Vsevolod Salnikov, Michael T. Schaub, Renaud Lambiotte:
Using higher-order Markov models to reveal flow-based communities in networks. CoRR abs/1601.03516 (2016) - [i8]Michael T. Schaub, Maguy Trefois, Paul Van Dooren, Jean-Charles Delvenne:
Sparse matrix factorizations for fast linear solvers with application to Laplacian systems. CoRR abs/1605.09148 (2016) - [i7]Michael T. Schaub, Neave O'Clery, Yazan N. Billeh, Jean-Charles Delvenne, Renaud Lambiotte, Mauricio Barahona:
Graph partitions and cluster synchronization in networks of oscillators. CoRR abs/1608.04283 (2016) - [i6]Michael T. Schaub, Jean-Charles Delvenne, Martin Rosvall, Renaud Lambiotte:
The many facets of community detection in complex networks. CoRR abs/1611.07769 (2016) - [i5]Ernesto Estrada, Jean-Charles Delvenne, Naomichi Hatano, José L. Mateos, Ralf Metzler, Alejandro P. Riascos, Michael T. Schaub:
Random Multi-Hopper Model. Super-Fast Random Walks on Graphs. CoRR abs/1612.08631 (2016) - 2015
- [j3]Michael T. Schaub, Yazan N. Billeh, Costas A. Anastassiou, Christof Koch, Mauricio Barahona:
Emergence of Slow-Switching Assemblies in Structured Neuronal Networks. PLoS Comput. Biol. 11(7) (2015) - 2014
- [j2]Michael T. Schaub, Jörg Lehmann, Sophia N. Yaliraki, Mauricio Barahona:
Structure of complex networks: Quantifying edge-to-edge relations by failure-induced flow redistribution. Netw. Sci. 2(1): 66-89 (2014) - 2013
- [i4]Michael T. Schaub, Jörg Lehmann, Sophia N. Yaliraki, Mauricio Barahona:
Structure of complex networks: Quantifying edge-to-edge relations by failure-induced flow redistribution. CoRR abs/1303.6241 (2013) - [i3]Jean-Charles Delvenne, Michael T. Schaub, Sophia N. Yaliraki, Mauricio Barahona:
The stability of a graph partition: A dynamics-based framework for community detection. CoRR abs/1308.1605 (2013) - 2012
- [j1]Michael T. Schaub, Simon R. Schultz:
The Ising decoder: reading out the activity of large neural ensembles. J. Comput. Neurosci. 32(1): 101-118 (2012) - 2011
- [i2]Michael T. Schaub, Jean-Charles Delvenne, Sophia N. Yaliraki, Mauricio Barahona:
Markov dynamics as a zooming lens for multiscale community detection: non clique-like communities and the field-of-view limit. CoRR abs/1109.5593 (2011) - [i1]Michael T. Schaub, Renaud Lambiotte, Mauricio Barahona:
Coding of Markov dynamics for multiscale community detection in complex networks. CoRR abs/1109.6642 (2011)
Coauthor Index
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