Network sampling in social graphs encompasses a suite of methodologies designed to extract representative subsets from large‐scale networks, enabling analysis when complete data are unavailable or ...
On Thursday the 21st of November 2019, M.Sc. Topi Talvitie will defend his doctoral thesis on Counting and Sampling Directed Acyclic Graphs for Learning Bayesian Networks. The thesis is a part of ...
On the 27th of September 2024, M.Sc. Juha Harvainen defends his PhD thesis on Advances in Sampling and Counting Bipartite Matchings and Directed Acyclic Graphs. The thesis is related to research done ...
Heterogeneous graph representation learning seeks to map complex networks containing multiple types of nodes and relations into low-dimensional vector spaces while preserving semantic, structural and, ...
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