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Martijn Gösgens
Martijn Gösgens
Verified email at student.tue.nl - Homepage
Title
Cited by
Cited by
Year
Good classification measures and how to find them
M Gösgens, A Zhiyanov, A Tikhonov, L Prokhorenkova
Advances in neural information processing systems 34, 17136-17147, 2021
262021
Systematic analysis of cluster similarity indices: How to validate validation measures
M Gösgens, A Tikhonov, L Prokhorenkova
International Conference on Machine Learning, 3799-3808, 2021
24*2021
Trade-offs between mobility restrictions and transmission of SARS-CoV-2
M Gösgens, T Hendriks, M Boon, W Steenbakkers, H Heesterbeek, ...
Journal of the Royal Society Interface 18 (175), 20200936, 2021
19*2021
The hyperspherical geometry of community detection: modularity as a distance
M Gösgens, R van der Hofstad, N Litvak
Journal of Machine Learning Research 24 (112), 1-36, 2023
72023
The role of inter-regional mobility in forecasting SARS-CoV-2 transmission
MHH Schoot Uiterkamp, M Gösgens, H Heesterbeek, R van der Hofstad, ...
Journal of the Royal Society Interface 19 (193), 20220486, 2022
62022
Correcting for granularity bias in modularity-based community detection methods
M Gösgens, R van der Hofstad, N Litvak
International Workshop on Algorithms and Models for the Web-Graph, 1-18, 2023
12023
Detecting small and large communities in networks
MM Gösgens
2024
The Erd\H {o} sR\'enyi Random Graph Conditioned on Every Component Being a Clique
M Gösgens, L Lüchtrath, E Magnanini, M Noy, É de Panafieu
arXiv preprint arXiv:2405.13454, 2024
2024
The Projection Method: a Unified Formalism for Community Detection
M Gösgens, R van der Hofstad, N Litvak
Frontiers in Complex Systems 2, 2024
2024
The Hyperspherical Geometry of Community Detection: Modularity as a Distance
MM Gösgens, RW van der Hofstad, NV Litvak
arXiv 2107, 1-29, 2022
2022
Dynamically adaptive age-based maintenance policies
M Gösgens, S Kolumbán, S Kapodistria
2018
Limit theorems for the Erdos–Rényi random graph conditioned on being a cluster graph
M Gösgens, L Lüchtrath, E Magnanini, M Noy, É de Panafieu
Evaluating graph generative models with graph kernels: what structural characteristics are captured?
M Gösgens, A Tikhonov, L Prokhorenkova
A framework for community detection
MM Gösgens
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Articles 1–14