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cs.LG2026
Boundary Variance Inflation Causes Acquisition Bias in Gaussian Processes
Maria Bånkestad, Sanna Jarl, Jens Sjölund
Gaussian processes with stationary kernels on bounded domains exhibit inflated posterior variance near the boundary. Despite being a long-recognized artifact in geostatistics and a…
cs.LG2026
Correcting Boundary Bias and Observation Independence in Bayesian Experimental Design
Sanna Jarl, Maria Bånkestad, Jonathan J. S. Scragg +1
In many experimental settings, active learning can improve sample efficiency by sequentially selecting where to measure, which is particularly valuable when experiments are expensi…
cs.LG2025
Machine learning for in-situ composition mapping in a self-driving magnetron sputtering system
Sanna Jarl, Jens Sjölund, Robert J. W. Frost +2
Self-driving labs (SDLs), employing automation and machine learning (ML) to accelerate experimental procedures, have enormous potential in the discovery of new materials. However,…