activity
20202026
collaborators

5 papers

stat.CO2026

TrunX: A massively parallel, differentiable implementation of the 3-PG forest growth model in JAX

Glory Mary Givi, Cédric Travelletti, Grégory Mermoud

Process-based forest models are widely used to simulate forest growth and responses to environmental change, but their calibration and application often require many computationall…

stat.ML2023

Non-Sequential Ensemble Kalman Filtering using Distributed Arrays

Cédric Travelletti, Jörg Franke, David Ginsbourger +1

This work introduces a new, distributed implementation of the Ensemble Kalman Filter (EnKF) that allows for non-sequential assimilation of large datasets in high-dimensional proble…

math.ST2022

Disintegration of Gaussian Measures for Sequential Assimilation of Linear Operator Data

Cédric Travelletti, David Ginsbourger

Gaussian processes appear as building blocks in various stochastic models and have been found instrumental to account for imprecisely known, latent functions. It is often the case…

stat.ML2021

Uncertainty Quantification and Experimental Design for Large-Scale Linear Inverse Problems under Gaussian Process Priors

Cédric Travelletti, David Ginsbourger, Niklas Linde

We consider the use of Gaussian process (GP) priors for solving inverse problems in a Bayesian framework. As is well known, the computational complexity of GPs scales cubically in…

stat.AP2020

Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling

Trygve Olav Fossum, Cédric Travelletti, Jo Eidsvik +2

Improving and optimizing oceanographic sampling is a crucial task for marine science and maritime resource management. Faced with limited resources in understanding processes in th…