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Thomas Rodet

2 accepted papers

2020

Unsupervised Variational Bayesian Kalman Filtering For Large-Dimensional Gaussian Systems

ICASSP 2020accepted

This paper considers the unsupervised filtering problem for large-dimensional linear and Gaussian systems, a setup in which the optimal Kalman filter (KF) might not be usable due to the exorbitant computational cost and storage requirements. For this problem, we propose two efficient algorithms base…

Cited by 0SourceScholar
2015

Efficient model choice and parameter estimation by using nested sampling applied in Eddy-Current Testing

ICASSP 2015accepted

In many applications, such as Eddy-Current Testing (ECT), we are often interested in the joint model choice and parameter estimation. Nested Sampling (NS) is one of the possible methods. The key step that reflects the efficiency of the NS algorithm is how to get samples with hard constraint on the l…

Cited by 0SourceScholar