3 papers
stat.ML2026
Piecewise Deterministic Markov Processes for Bayesian Neural Networks
Ethan Goan, Dimitri Perrin, Kerrie Mengersen +1
Inference on modern Bayesian Neural Networks (BNNs) often relies on a variational inference treatment, imposing violated assumptions of independence and the form of the posterior.…
cs.DS2025
Optimal Clustering with Dependent Costs in Bayesian Networks
Paul Pao-Yen Wu, Fabrizio Ruggeri, Kerrie Mengersen
Background: Clustering of nodes in Bayesian Networks (BNs) and related graphical models such as Dynamic BNs (DBNs) has been demonstrated to enhance computational efficiency and imp…
cs.CL2025
AIMS.au: A Dataset for the Analysis of Modern Slavery Countermeasures in Corporate Statements
Adriana Eufrosina Bora, Pierre-Luc St-Charles, Mirko Bronzi +3
Despite over a decade of legislative efforts to address modern slavery in the supply chains of large corporations, the effectiveness of government oversight remains hampered by the…