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Covers graphical models for probabilistic distributions using graphs, nodes, and edges.
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Explores consensus algorithms in digraphs, focusing on scenarios where the digraph is not strongly connected.
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Explores link prediction in networks, covering missing edges, probabilistic methods, and causal inference challenges.
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Science-fiction: Hybridity
Delves into hybridity in science-fiction, exploring space opera and science-fantasy themes like hard science and cyberpunk.
Graphical Models: Probability Distributions and Factor Graphs
Covers graphical models for probability distributions and factor graphs representation.
Statistical Analysis of Network Data
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