Zobrazeno 1 - 10
of 11 906
pro vyhledávání: '"Pernot"'
Publikováno v:
ClinicoEconomics and Outcomes Research, Vol Volume 13, Pp 53-63 (2021)
Alexandre Le Guyader,1 Mathieu Pernot,2 Clément Delmas,3 Stéphane Roze,4 Isabelle Fau,5 Erwan Flecher,6 Guillaume Lebreton7 1Department of Thoracic and Cardiovascular Surgery, Dupuytren University Hospital, Limoges, France; 2Department of Cardiolog
Externí odkaz:
https://doaj.org/article/75ab023e31e046dc8b832d8f4d0f9d5c
Publikováno v:
IEEE Electron Device Letters, 2024, pp.1-1.
This letter presents the bulk diamond field-effect transistor (FET) with the highest current value reported at this moment. The goal was to drastically increase the current of this type of device by increasing the total gate width thanks to an interd
Externí odkaz:
http://arxiv.org/abs/2409.03293
Autor:
Pernot, Pascal
This short study presents an opportunistic approach to a (more) reliable validation method for prediction uncertainty average calibration. Considering that variance-based calibration metrics (ZMS, NLL, RCE...) are quite sensitive to the presence of h
Externí odkaz:
http://arxiv.org/abs/2408.13089
Autor:
Swami, R., Julie, G., Le-Denmat, S., Pernot, G., Singhal, D., Paterson, J., Maire, J., Motte, J. F., Paillet, N., Guillou, H., Gomes, S., Bourgeois, O.
Scanning Thermal Microscopy (SThM) has become an important measurement tool for characterizing the thermal properties of materials at the nanometer scale. This technique requires a SThM probe that combines an Atomic Force Microscopy (AFM) probe and a
Externí odkaz:
http://arxiv.org/abs/2403.05405
Autor:
Pernot, Pascal
Some popular Machine Learning Uncertainty Quantification (ML-UQ) calibration statistics do not have predefined reference values and are mostly used in comparative studies. In consequence, calibration is almost never validated and the diagnostic is le
Externí odkaz:
http://arxiv.org/abs/2403.00423
Autor:
Pernot, Pascal
Average calibration of the (variance-based) prediction uncertainties of machine learning regression tasks can be tested in two ways: one is to estimate the calibration error (CE) as the difference between the mean absolute error (MSE) and the mean va
Externí odkaz:
http://arxiv.org/abs/2402.10043
Autor:
Pernot, Allan John
As our climate continues to shift, it is fundamental to understanding these unprecedented changes through field research done in biomes most critically impacted. Due to the remoteness and extreme climatic nature of these research stations, they are t
Externí odkaz:
http://hdl.handle.net/10919/115822
Autor:
Baccile, Niki, Poirier, Alexandre, Griel, Patrick Le, Pernot, Petra, Pala, Melike, Roelants, Sophie, Soetaert, Wim, Stevens, Christian
Publikováno v:
Colloids and Surfaces A: Physicochemical and Engineering Aspects
Sophorolipids are well-known scaled-up microbial glycolipid biosurfactants with a strong potential for commercialization due to their biological origin and mildness in contact with the skin and the environment compared to classical surfactants. Howev
Externí odkaz:
http://arxiv.org/abs/2310.14727
Autor:
Pernot, Pascal
Binwise Variance Scaling (BVS) has recently been proposed as a post hoc recalibration method for prediction uncertainties of machine learning regression problems that is able of more efficient corrections than uniform variance (or temperature) scalin
Externí odkaz:
http://arxiv.org/abs/2310.11978
Autor:
Pernot, Pascal
Publikováno v:
APL Mach. Learn. 1:046121 (2023)
Reliable uncertainty quantification (UQ) in machine learning (ML) regression tasks is becoming the focus of many studies in materials and chemical science. It is now well understood that average calibration is insufficient, and most studies implement
Externí odkaz:
http://arxiv.org/abs/2309.06240