An IPM-based framework for Bayesian optimal experimental design is proposed that replaces KL-based expected information gain with Wasserstein, MMD, and energy distances, delivering stronger stability guarantees and plug-and-play extensions.
Observationally informed adaptive causal experimental de- sign.arXiv preprint arXiv:2603.03785
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Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions
An IPM-based framework for Bayesian optimal experimental design is proposed that replaces KL-based expected information gain with Wasserstein, MMD, and energy distances, delivering stronger stability guarantees and plug-and-play extensions.