3 papers
cs.LG2026
Learning Bayesian and Markov Networks with an Unreliable Oracle
Juha Harviainen, Pekka Parviainen, Vidya Sagar Sharma
We study constraint-based structure learning of Markov networks and Bayesian networks in the presence of an unreliable conditional independence oracle that makes at most a bounded…
cs.LG2026
Evaluating Prediction Uncertainty Estimates from BatchEnsemble
Morten Blørstad, Herman Jangsett Mostein, Nello Blaser +1
Deep learning models struggle with uncertainty estimation. Many approaches are either computationally infeasible or underestimate uncertainty. We investigate \textit{BatchEnsemble}…
cs.DS2025
Graph Reconstruction with a Connected Components Oracle
Juha Harviainen, Pekka Parviainen
In the Graph Reconstruction (GR) problem, the goal is to recover a hidden graph by utilizing some oracle that provides limited access to the structure of the graph. The interest is…