most citedLearning signals defined on graphs with optimal transport and Gaussian process regression

1 citations

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3 papers

stat.ML2025

A reproducible comparative study of categorical kernels for Gaussian process regression, with new clustering-based nested kernels

Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier

Designing categorical kernels is a major challenge for Gaussian process regression with continuous and categorical inputs. Despite previous studies, it is difficult to identify a p…

stat.ML2024★ 1 cited

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…

cs.NI2024

Perfect simulation of Markovian load balancing queueing networks in equilibrium

Carl Graham

We define a wide class of Markovian load balancing networks of identical single-server infinite-buffer queues. These networks may implement classic parallel server or work stealing…