Pernot, Pascal

1. Properties of the ENCE and other MAD-based calibration metrics
   2023/05/17 by Pernot, Pascal · 2 citations
   #Chemical Physics (physics.chem-ph) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Methodology (stat.ME) #Statistics and Probability (physics.data-an)
2. Acknowledging user requirements for accuracy in computational chemistry benchmarks
   2020/04/01 by Andreas Savin, Pascal Pernot, Savin, Andreas +1 · 1 citation
   Computer Science · Decision Sciences · Materials Science · #Chemical Physics (physics.chem-ph) #Computational Drug Discovery Methods #Data Analysis #FOS: Physical sciences #Machine Learning in Materials Science #Scientific Computing and Data Management #Statistics and Probability (physics.data-an)
3. Confidence curves for UQ validation: probabilistic reference vs. oracle
   2022/06/30 by Pernot, Pascal · 1 citation
   #Data Analysis #FOS: Physical sciences #Statistics and Probability (physics.data-an)
4. Validation of uncertainty quantification metrics: a primer based on the consistency and adaptivity concepts
   2023/03/13 by Pascal Pernot, Pernot, Pascal · 1 citation
   Decision Sciences · Engineering · Materials Science · #Chemical Physics (physics.chem-ph) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Fault Detection and Control Systems #Machine Learning (stat.ML) #Machine Learning in Materials Science #Scientific Measurement and Uncertainty Evaluation #Statistics and Probability (physics.data-an)
5. Can bin-wise scaling improve consistency and adaptivity of prediction uncertainty for machine learning regression ?
   2023/10/18 by Pascal Pernot, Pernot, Pascal · 1 citation
   Computer Science · Materials Science · #Chemical Physics (physics.chem-ph) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Machine Learning in Materials Science #Neural Networks and Applications #Statistics and Probability (physics.data-an)