Pascal Pernot

11 papers Journal 11

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	How to validate average calibration for machine learning regression tasks ? CoRR Pascal Pernot
2024	J	`jnl`	On the good reliability of an interval-based metric to validate prediction uncertainty for machine learning regression tasks. CoRR Pascal Pernot
2024	J	`jnl`	Validation of ML-UQ calibration statistics using simulated reference values: a sensitivity analysis. CoRR Pascal Pernot
2023	J	`jnl`	Can bin-wise scaling improve consistency and adaptivity of prediction uncertainty for machine learning regression ? CoRR Pascal Pernot
2023	J	`jnl`	Consistency and adaptivity are complementary targets for the validation of variance-based uncertainty quantification metrics in machine learning regression tasks. CoRR Pascal Pernot
2023	J	`jnl`	Properties of the ENCE and other MAD-based calibration metrics. CoRR Pascal Pernot
2022	J	`jnl`	Should We Gain Confidence from the Similarity of Results between Methods? Comput. Pascal Pernot, Andreas Savin
2021	J	`jnl`	Corrigendum: Impact of non-normal error distributions on the benchmarking and ranking of quantum machine learning models (2020 Mach. Learn.: Sci. Technol. 1 035011). Mach. Learn. Sci. Technol. Pascal Pernot, Bing Huang, Andreas Savin
2020	J	`jnl`	Impact of non-normal error distributions on the benchmarking and ranking of quantum machine learning models. Mach. Learn. Sci. Technol. Pascal Pernot, Bing Huang, Andreas Savin
2016	J	`jnl`	On the Use of Benchmarks for Multiple Properties. Comput. Bartolomeo Civalleri, Roberto Dovesi, Pascal Pernot, Davide Presti, Andreas Savin
2014	J	`jnl`	Calibration of forcefields for molecular simulation: Sequential design of computer experiments for building cost-efficient kriging metamodels. J. Comput. Chem. Fabien Cailliez, Arnaud Bourasseau, Pascal Pernot