Sort by
Refine Your Search
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
solving complex inverse problems that link measurements to their underlying causes. This PhD interdisciplinary programme focuses on Bayesian methods for estimating physical parameters from high-dimensional
-
) relationship with the low-fidelity response. Extensions include nonlinear information fusion with GPs, Bayesian multi-fidelity inference and deep probabilistic surrogates, as well as MF neural networks
-
lattice orientation by EBSD or local chemical composition by EDX [1]. For instance, an original protocol based on Bayesian inference was recently co-developed by LEM3 and ICA to determine the single-crystal
-
of variable distributions [13,14]. Graphic neural networks (GNNs) are new inference methods developed in recent years and are attracting increasing attention due to their efficiency and ability in solving
-
stochastic modeling, Bayesian inference, data fusion and modern machine learning. Its research activities span various application domains such as security, non-destructive testing, infrared imaging and