Chapter 1: Mapping low-resolution edges to high-resolution paths: the case of traffic measurements in cities.
Chapter 2: From Low Resource Information Extraction to Identifying Influential Nodes in Knowledge Graphs.
Chapter 3: Inhomogenous Marketing Mix Diffusion.
Chapter 4: Modelling both pairwise interactions and group effects in polarization on interaction networks.
Chapter 5: Computing Motifs in Hypergraphs.
Chapter 6: Extending network tools to explore trends in temporal granular trade networks.
Chapter 7: Expressivity of Geometric Inhomogeneous Random Graphs-Metric and Non-Metric.
Chapter 8: Social Interactions Matter: Is Grey Wolf Optimizer a Particle Swarm Optimization Variation?.
Chapter 9: Exploring Ingredient Variability in Classic Russian Cuisine Dishes through Complex Network Analysis.
Chapter 10: Unraveling the Structure of Knowledge: Consistency in Everyday Networks, Diversity in Scientific.
Chapter 11: Kinetic-based force-directed graph embedding.
Chapter12: Deep Graph Machine Learning Models for Epidemic Spread Prediction and Prevention.
Chapter 13: EleMi: A robust method to infer soil ecological networks with better community structure.
Chapter 14: Interpreting Node Embedding Distances Through n-order Proximity Neighbourhoods.
Chapter 15: Edge Dismantling with Geometric Reinforcement Learning.
Chapter 16: Public Transit Inequality in the Context of the Built Environment.
