| 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 | 21 | 2021 |
| 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 | 21* | 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 | 7 | 2023 |
| 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 | 5 | 2022 |
| 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 | 1 | 2023 |
| The Projection Method: a Unified Formalism for Community Detection M Gösgens, R van der Hofstad, N Litvak Frontiers in Complex Systems 2, 2024 | | 2024 |
| Evaluating graph generative models with graph kernels: what structural characteristics are captured? M Gösgens, A Tikhonov, L Prokhorenkova | | 2023 |
| Containment strategies after the first wave of COVID-19 using mobility data (preprint) M Gösgens, T Hendriks, M Boon, S Keuning, W Steenbakkers, ... | | 2020 |
| Dynamically adaptive age-based maintenance policies M Gösgens, S Kolumbán, S Kapodistria | | 2018 |
| A framework for community detection MM Gösgens | | |
