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stat.ML2024★ 1 cited
Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees
Edgar Jaber, Vincent Blot, Nicolas Brunel +6
Gaussian processes (GPs) are a Bayesian machine learning approach widely used to construct surrogate models for the uncertainty quantification of computer simulation codes in indus…
stat.ML2022★ 18 cited
MAPIE: an open-source library for distribution-free uncertainty quantification
Vianney Taquet, Vincent Blot, Thomas Morzadec +2
Estimating uncertainties associated with the predictions of Machine Learning (ML) models is of crucial importance to assess their robustness and predictive power. In this submissio…