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stat.ML2025
CRPS-Based Targeted Sequential Design with Application in Chemical Space
Lea Friedli, Athénaïs Gautier, Anna Broccard +1
Sequential design of real and computer experiments via Gaussian Process (GP) models has proven useful for parsimonious, goal-oriented data acquisition purposes. In this work, we fo…
stat.ML2024
Efficient pooling of predictions via kernel embeddings
Sam Allen, David Ginsbourger, Johanna Ziegel
Probabilistic predictions are probability distributions over the set of possible outcomes. Such predictions quantify the uncertainty in the outcome, making them essential for effec…