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09/21/2023
Model-based Clustering using Non-parametric Hidden Markov Models
Thanks to their dependency structure, non-parametric Hidden Markov Model...
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06/28/2023
Frontiers to the learning of nonparametric hidden Markov models
Hidden Markov models (HMMs) are flexible tools for clustering dependent ...
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04/19/2023
Support and distribution inference from noisy data
We consider noisy observations of a distribution with unknown support. I...
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06/01/2022
Amortized backward variational inference in nonlinear state-space models
We consider the problem of state estimation in general state-space model...
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03/01/2022
Deconvolution of spherical data corrupted with unknown noise
We consider the deconvolution problem for densities supported on a (d-1)...
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06/24/2021
Fundamental limits for learning hidden Markov model parameters
We study the frontier between learnable and unlearnable hidden Markov mo...
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06/17/2021
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA
We introduce a new general identifiable framework for principled disenta...
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02/16/2021
Joint self-supervised blind denoising and noise estimation
We propose a novel self-supervised image blind denoising approach in whi...
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01/11/2021
Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach
Given a nonparametric Hidden Markov Model (HMM) with two states, the que...
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06/25/2020
Deconvolution with unknown noise distribution is possible for multivariate signals
This paper considers the deconvolution problem in the case where the tar...
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02/04/2019
Identifiability and consistent estimation of nonparametric translation hidden Markov models with general state space
In this paper, we consider partially observed dynamical systems where th...
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11/05/2018
Mixture of generalized linear models: identifiability and applications
We consider finite mixtures of generalized linear models with binary out...
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01/12/2018