| Machine learning meets complex networks via coalescent embedding in the hyperbolic space A Muscoloni, JM Thomas, S Ciucci, G Bianconi, CV Cannistraci Nature Communications 8 (1), 1, 2017 | 203 | 2017 |
| A nonuniform popularity-similarity optimization (nPSO) model to efficiently generate realistic complex networks with communities A Muscoloni, CV Cannistraci New Journal of Physics 20 (5), 052002, 2018 | 99 | 2018 |
| Modular gateway-ness connectivity and structural core organization in maritime network science M Xu, Q Pan, A Muscoloni, H Xia, CV Cannistraci Nature communications 11 (1), 2849, 2020 | 63 | 2020 |
| Leveraging the nonuniform PSO network model as a benchmark for performance evaluation in community detection and link prediction A Muscoloni, CV Cannistraci New Journal of Physics 20 (6), 063022, 2018 | 49 | 2018 |
| Functional brain network topology discriminates between patients with minimally conscious state and unresponsive wakefulness syndrome A Cacciola, A Naro, D Milardi, A Bramanti, L Malatacca, M Spitaleri, A Leo, ... Journal of clinical medicine 8 (3), 306, 2019 | 44 | 2019 |
| Local-community network automata modelling based on length-three-paths for prediction of complex network structures in protein interactomes, food webs and more A Muscoloni, I Abdelhamid, CV Cannistraci BioRxiv, 346916, 2018 | 43 | 2018 |
| Navigability evaluation of complex networks by greedy routing efficiency A Muscoloni, CV Cannistraci Proceedings of the National Academy of Sciences 116 (5), 1468-1469, 2019 | 32 | 2019 |
| Local-ring network automata and the impact of hyperbolic geometry in complex network link-prediction A Muscoloni, U Michieli, CV Cannistraci arXiv preprint arXiv:1707.09496, 2017 | 27 | 2017 |
| Coalescent embedding in the hyperbolic space unsupervisedly discloses the hidden geometry of the brain A Cacciola, A Muscoloni, V Narula, A Calamuneri, S Nigro, EA Mayer, ... arXiv preprint arXiv:1705.04192, 2017 | 27 | 2017 |
| Proprotein convertase subtilisin/kexin 9 (PCSK9) promotes macrophage activation via LDL receptor-independent mechanisms S Katsuki, P K. Jha, A Lupieri, T Nakano, LSA Passos, MA Rogers, ... Circulation research 131 (11), 873-889, 2022 | 25 | 2022 |
| Minimum curvilinear automata with similarity attachment for network embedding and link prediction in the hyperbolic space A Muscoloni, CV Cannistraci arXiv preprint arXiv:1802.01183, 2018 | 21 | 2018 |
| Can local-community-paradigm and epitopological learning enhance our understanding of how local brain connectivity is able to process, learn and memorize chronic pain? V Narula, AG Zippo, A Muscoloni, GEM Biella, CV Cannistraci Applied Network Science 2, 1-28, 2017 | 21 | 2017 |
| Adaptive network automata modelling of complex networks A Muscoloni, U Michieli, Y Zhang, CV Cannistraci Preprints, 2022 | 19 | 2022 |
| Rich-clubness test: how to determine whether a complex network has or doesn't have a rich-club? A Muscoloni, CV Cannistraci arXiv preprint arXiv:1704.03526, 2017 | 15 | 2017 |
| Real-time tracking with an embedded 3D camera with FPGA processing A Muscoloni, S Mattoccia 2014 international conference on 3d imaging (IC3D), 1-7, 2014 | 15 | 2014 |
| Angular separability of data clusters or network communities in geometrical space and its relevance to hyperbolic embedding A Muscoloni, CV Cannistraci arXiv preprint arXiv:1907.00025, 2019 | 12 | 2019 |
| Geometrical congruence, greedy navigability and myopic transfer in complex networks and brain connectomes CV Cannistraci, A Muscoloni Nature Communications 13 (1), 7308, 2022 | 9 | 2022 |
| Geometrical inspired pre-weighting enhances Markov clustering community detection in complex networks C Durán, A Muscoloni, CV Cannistraci Applied Network Science 6 (1), 29, 2021 | 8 | 2021 |
| Early retrieval problem and link prediction evaluation via the area under the magnified ROC A Muscoloni, CV Cannistraci Preprints, 2022 | 6 | 2022 |
| Short note on comparing stacking modelling versus cannistraci-hebb adaptive network automata for link prediction in complex networks A Muscoloni, CV Cannistraci Preprints, 2021 | 6 | 2021 |
Carlo Vittorio CannistraciChair Professor & Chief Scientist, Center for Complex Network Intelligence, Tsinghua UniversityBestätigte E-Mail-Adresse bei mail.tsinghua.edu.cn
