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math.ST2024
Deconvolution of repeated measurements corrupted by unknown noise
Jérémie Capitao-Miniconi, Elisabeth Gassiat, Luc Lehéricy
Recent advances have demonstrated the possibility of solving the deconvolution problem without prior knowledge of the noise distribution. In this paper, we study the repeated measu…
math.ST2023
Support and distribution inference from noisy data
Jérémie Capitao-Miniconi, Elisabeth Gassiat, Luc Lehéricy
We consider noisy observations of a distribution with unknown support. In the deconvolution model, it has been proved recently [19] that, under very mild assumptions, it is possibl…
math.ST2020
Deconvolution with unknown noise distribution is possible for multivariate signals
Elisabeth Gassiat, Sylvain Le Corff, Luc Lehéricy
This paper considers the deconvolution problem in the case where the target signal is multidimensional and no information is known about the noise distribution. More precisely, no…