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Angus Phillips

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Jul 2026

Bayesian Experimental Design via Score Matching

This work shows that the double intractability of the EIG can be isolated from the policy learning by first solving a score matching problem that is independent of the policy used, then using the learned score approximation to train the policy in a singly intractable manner.

Angus Phillips, Gavin Kerrigan, Tom Rainforth · 0 citations

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