Graph-based data clustering via multiscale community detection
Z Liu, M Barahona - Applied Network Science, 2020 - Springer
We present a graph-theoretical approach to data clustering, which combines the creation of
a graph from the data with Markov Stability, a multiscale community detection framework. We …
a graph from the data with Markov Stability, a multiscale community detection framework. We …
Unfolding the multiscale structure of networks with dynamical Ollivier-Ricci curvature
A Gosztolai, A Arnaudon - Nature Communications, 2021 - nature.com
Describing networks geometrically through low-dimensional latent metric spaces has helped
design efficient learning algorithms, unveil network symmetries and study dynamical …
design efficient learning algorithms, unveil network symmetries and study dynamical …
Overlapping community detection on complex networks with Graph Convolutional Networks
S Yuan, H Zeng, Z Zuo, C Wang - Computer Communications, 2023 - Elsevier
Discovering the community structure within networks is of significance with respect to many
realistic applications, like recommendation systems and cyberattack detection. In this study …
realistic applications, like recommendation systems and cyberattack detection. In this study …
Data-driven unsupervised clustering of online learner behaviour
The widespread adoption of online courses opens opportunities for analysing learner
behaviour and optimising web-based learning adapted to observed usage. Here, we …
behaviour and optimising web-based learning adapted to observed usage. Here, we …
Toward precision healthcare: context and mathematical challenges
Precision medicine refers to the idea of delivering the right treatment to the right patient at
the right time, usually with a focus on a data-centered approach to this task. In this …
the right time, usually with a focus on a data-centered approach to this task. In this …
Flow-Based Network Analysis of the Caenorhabditis elegans Connectome
We exploit flow propagation on the directed neuronal network of the nematode C. elegans to
reveal dynamically relevant features of its connectome. We find flow-based groupings of …
reveal dynamically relevant features of its connectome. We find flow-based groupings of …
From free text to clusters of content in health records: an unsupervised graph partitioning approach
Electronic healthcare records contain large volumes of unstructured data in different forms.
Free text constitutes a large portion of such data, yet this source of richly detailed information …
Free text constitutes a large portion of such data, yet this source of richly detailed information …
Community detection with graph neural network using Markov stability
S Yuan, C Wang, Q Jiang, J Ma - … International Conference on …, 2022 - ieeexplore.ieee.org
Community detection is a fundamental task in network analysis. With the recent
development of deep learning, some community detection methods related to deep learning …
development of deep learning, some community detection methods related to deep learning …
New geographic model of care to manage the post-COVID-19 elective surgery aftershock in England: a retrospective observational study
Objectives The suspension of elective surgery during the COVID-19 pandemic is
unprecedented and has resulted in record volumes of patients waiting for operations. Novel …
unprecedented and has resulted in record volumes of patients waiting for operations. Novel …
Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks
Background Recent advances in single-cell RNA sequencing have allowed researchers to
explore transcriptional function at a cellular level. In particular, single-cell RNA sequencing …
explore transcriptional function at a cellular level. In particular, single-cell RNA sequencing …