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stat.ML2025
Approximation of differential entropy in Bayesian optimal experimental design
Chuntao Chen, Tapio Helin, Nuutti Hyvönen +1
Bayesian optimal experimental design provides a principled framework for selecting experimental configurations that maximize obtained information. In this work, we consider setting…
math.NA2025
Lattice Rules Meet Kernel Cubature
Vesa Kaarnioja, Ilja Klebanov, Claudia Schillings +1
Rank-1 lattice rules are a class of equally weighted quasi-Monte Carlo methods that achieve essentially linear convergence rates for functions in a reproducing kernel Hilbert space…