1 citations · 1 across the 3 of their papers we have counts for
4 papers
Asymmetric conformal prediction with penalized kernel sum-of-squares
Louis Allain, Sébastien Da Veiga, Brian Staber
Conformal prediction (CP) is a distribution-free method to construct reliable prediction intervals that has gained significant attention in recent years. Despite its success and va…
Distributional encoding for Gaussian process regression with qualitative inputs
Sébastien Da Veiga
Gaussian Process (GP) regression is a popular and sample-efficient approach for many engineering applications, where observations are expensive to acquire, and is also a central in…
Scalable and adaptive prediction bands with kernel sum-of-squares
Louis Allain, Sébastien da Veiga, Brian Staber
Conformal Prediction (CP) is a popular framework for constructing prediction bands with valid coverage in finite samples, while being free of any distributional assumption. A well-…
Learning signals defined on graphs with optimal transport and Gaussian process regression
Raphaël Carpintero Perez, Sébastien da Veiga, Josselin Garnier +1
In computational physics, machine learning has now emerged as a powerful complementary tool to explore efficiently candidate designs in engineering studies. Outputs in such supervi…