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Pascal Pernot
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Journal Articles
- 2022
- [j5]Pascal Pernot, Andreas Savin:
Should We Gain Confidence from the Similarity of Results between Methods? Comput. 10(2): 27 (2022) - 2021
- [j4]Pascal Pernot, Bing Huang, Andreas Savin:
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. 2(1): 19501 (2021) - 2020
- [j3]Pascal Pernot, Bing Huang, Andreas Savin:
Impact of non-normal error distributions on the benchmarking and ranking of quantum machine learning models. Mach. Learn. Sci. Technol. 1(3): 35011 (2020) - 2016
- [j2]Bartolomeo Civalleri, Roberto Dovesi, Pascal Pernot, Davide Presti, Andreas Savin:
On the Use of Benchmarks for Multiple Properties. Comput. 4(2): 20 (2016) - 2014
- [j1]Fabien Cailliez, Arnaud Bourasseau, Pascal Pernot:
Calibration of forcefields for molecular simulation: Sequential design of computer experiments for building cost-efficient kriging metamodels. J. Comput. Chem. 35(2): 130-149 (2014)
Informal and Other Publications
- 2024
- [i5]Pascal Pernot:
How to validate average calibration for machine learning regression tasks ? CoRR abs/2402.10043 (2024) - [i4]Pascal Pernot:
Validation of ML-UQ calibration statistics using simulated reference values: a sensitivity analysis. CoRR abs/2403.00423 (2024) - 2023
- [i3]Pascal Pernot:
Properties of the ENCE and other MAD-based calibration metrics. CoRR abs/2305.11905 (2023) - [i2]Pascal Pernot:
Consistency and adaptivity are complementary targets for the validation of variance-based uncertainty quantification metrics in machine learning regression tasks. CoRR abs/2309.06240 (2023) - [i1]Pascal Pernot:
Can bin-wise scaling improve consistency and adaptivity of prediction uncertainty for machine learning regression ? CoRR abs/2310.11978 (2023)
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