Arnaud Vadeboncoeur

According to our database, Arnaud Vadeboncoeur authored at least 9 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Hierarchical Inference and Closure Learning via Adaptive Surrogates for ODEs and PDEs.

Pengyu Zhang, Arnaud Vadeboncoeur, Alex Glyn-Davies, Mark Girolami

CoRR, March, 2026

2025

Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later.

Arnaud Vadeboncoeur, Gregory Duthé, Mark Girolami, Eleni N. Chatzi

CoRR, September, 2025

Efficient Deconvolution in Populational Inverse Problems.

Arnaud Vadeboncoeur, Mark Girolami, Andrew M. Stuart

CoRR, May, 2025

Probabilistic Super-Resolution for High-Fidelity Physical System Simulations with Uncertainty Quantification.

Pengyu Zhang, Connor Duffin, Alex Glyn-Davies, Arnaud Vadeboncoeur, Mark Girolami

CoRR, February, 2025

Efficient Prior Calibration from Indirect Data.

Ömer Deniz Akyildiz, Mark Girolami, Andrew M. Stuart, Arnaud Vadeboncoeur

SIAM J. Sci. Comput., 2025

2024

A Primer on Variational Inference for Physics-Informed Deep Generative Modelling.

Alex Glyn-Davies, Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami

CoRR, 2024

2023

Fully probabilistic deep models for forward and inverse problems in parametric PDEs.

Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak

J. Comput. Phys., October, 2023

Random Grid Neural Processes for Parametric Partial Differential Equations.

Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz

Proceedings of the International Conference on Machine Learning, 2023

2022

Deep Probabilistic Models for Forward and Inverse Problems in Parametric PDEs.

Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak

CoRR, 2022