96 citations · 328 across the 30 of their papers we have counts for
4 papers · 1 filter
Influence and Influenceability: Global Directionality in Directed Complex Networks
Niall Rodgers, Peter Tino, Samuel Johnson
Knowing which nodes are influential in a complex network and whether the network can be influenced by a small subset of nodes is a key part of network analysis. However, many tradi…
Strong Connectivity in Real Directed Networks
Niall Rodgers, Peter Tino, Samuel Johnson
In many real, directed networks, the strongly connected component of nodes which are mutually reachable is very small. This does not fit with current theory, based on random graphs…
Interpretable Models Capable of Handling Systematic Missingness in Imbalanced Classes and Heterogeneous Datasets
Sreejita Ghosh, Elizabeth S. Baranowski, Michael Biehl +3
Application of interpretable machine learning techniques on medical datasets facilitate early and fast diagnoses, along with getting deeper insight into the data. Furthermore, the…
Network Hierarchy and Pattern Recovery in Directed Sparse Hopfield Networks
Niall Rodgers, Peter Tino, Samuel Johnson
Many real-world networks are directed, sparse and hierarchical, with a mixture of feed-forward and feedback connections with respect to the hierarchy. Moreover, a small number of '…