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Sébastien Combrexelle

4 accepted papers

2020

Iterative energy-based projection on a normal data manifold for anomaly localization

ICLR 2020poster

Autoencoder reconstructions are widely used for the task of unsupervised anomaly localization. Indeed, an autoencoder trained on normal data is expected to only be able to reconstruct normal features of the data, allowing the segmentation of anomalous pixels in an image via a simple comparison betwe…

Cited by 213SourceScholar
2017

Multivariate scale-free dynamics: Testing fractal connectivity

ICASSP 2017accepted

Scale-free dynamics commonly appear in individual components of multivariate data. Yet, while the behavior of cross-components is crucial in modeling real-world multivariate data, their examination often suggests departures from exact multivariate self-similarity (also termed fractal connectivity).…

Cited by 4SourceScholar
2016

A Bayesian framework for the multifractal analysis of images using data augmentation and a whittle approximation

ICASSP 2016accepted

Texture analysis is an image processing task that can be conducted using the mathematical framework of multifractal analysis to study the regularity fluctuations of image intensity and the practical tools for their assessment, such as (wavelet) leaders. A recently introduced statistical model for le…

Cited by 0SourceScholar
2015

A Bayesian approach for the joint estimation of the multifractality parameter and integral scale based on the Whittle approximation

ICASSP 2015accepted

Multifractal analysis is a powerful tool used in signal processing. Multifractal models are essentially characterized by two parameters, the multifractality parameter c2 and the integral scale A (the time scale beyond which multifractal properties vanish). Yet, most applications concentrate on estim…

Cited by 3SourceScholar