3 papers
cs.LG2025
Goal-Oriented Sequential Bayesian Experimental Design for Causal Learning
Zheyu Zhang, Jiayuan Dong, Jie Liu +1
We present GO-CBED, a goal-oriented Bayesian framework for sequential causal experimental design. Unlike conventional approaches that select interventions aimed at inferring the fu…
cs.LG2025
Variational Bayesian Optimal Experimental Design with Normalizing Flows
Jiayuan Dong, Christian Jacobsen, Mehdi Khalloufi +4
Bayesian optimal experimental design (OED) seeks experiments that maximize the expected information gain (EIG) in model parameters. Directly estimating the EIG using nested Monte C…
stat.ML2024
Variational Sequential Optimal Experimental Design using Reinforcement Learning
Wanggang Shen, Jiayuan Dong, Xun Huan
We present variational sequential optimal experimental design (vsOED), a novel method for optimally designing a finite sequence of experiments within a Bayesian framework with info…