Graphical models form a cornerstone of modern data analysis by providing a visually intuitive framework to represent and reason about the complex interdependencies among variables. In particular, ...
Recent advances in empirical finance have shown that the adoption of network theory is critical in order to understand contagion and systemic vulnerabilities. While interdependencies among financial ...
A Bayesian network is a directed acyclic graph (DAG) or a probabilistic graphical model used by statisticians. Vertices of this model represent different variables. Any connections between variables ...
On Friday the 24th of January 2020, M.Sc. Janne Leppä-aho will defend his doctoral thesis on Methods for Learning Directed and Undirected Graphical Models. The thesis is a part of research done in the ...
Concr CEO Irina Babina and CTO Matthew Griffiths unpack how Bayesian foundation models can excel at uncertainty management to ...
On the 8th of December 2021, M.Sc. Kari Rantanen will defend his doctoral thesis on Optimization Algorithms for Learning Graphical Model Structures. The thesis a part of research done in the ...
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