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stat.ML2025
Online Bayesian Experimental Design for Partially Observed Dynamical Systems
Sara Pérez-Vieites, Sahel Iqbal, Simo Särkkä +1
Bayesian experimental design (BED) provides a principled framework for optimizing data collection by choosing experiments that are maximally informative about unknown parameters. H…
cs.LG2025
Sequential Monte Carlo for Policy Optimization in Continuous POMDPs
Hany Abdulsamad, Sahel Iqbal, Simo Särkkä
Optimal decision-making under partial observability requires agents to balance reducing uncertainty (exploration) against pursuing immediate objectives (exploitation). In this pape…