Yohan Petetin

34 papers B 1C 3Misc 2Journal 16Unranked 12
YearRankTypeTitle / Venue / Authors
2025 J jnl
Adaptive Sample Sharing for Linear Regression.
CoRR
Hamza Cherkaoui, Hélène Halconruy, Yohan Petetin
2024 C conf
An Analysis of the Mutual Information Upper Bound for Sensor-Subset Selection.
FUSION
Idyano Leroy, Augustin A. Saucan, Yohan Petetin, Daniel Clark
2023 — conf
A Probabilistic Semi-Supervised Approach with Triplet Markov Chains.
MLSP
Katherine Morales, Yohan Petetin
2023 J jnl
A Probabilistic Semi-Supervised Approach with Triplet Markov Chains.
CoRR
Katherine Morales, Yohan Petetin
2023 J jnl
Deep parameterizations of pairwise and triplet Markov models for unsupervised classification of sequential data.
Comput. Stat. Data Anal.
Hugo Gangloff, Katherine Morales, Yohan Petetin
2023 J jnl
Expressivity of Hidden Markov Chains vs. Recurrent Neural Networks From a System Theoretic Viewpoint.
IEEE Trans. Signal Process.
François Desbouvries, Yohan Petetin, Achille Salaün
2022 J jnl
Expressivity of Hidden Markov Chains vs. Recurrent Neural Networks from a system theoretic viewpoint.
CoRR
François Desbouvries, Yohan Petetin, Achille Salaün
2021 — conf
A General Parametrization Framework for Pairwise Markov Models: An Application to Unsupervised Image Segmentation.
MLSP
Hugo Gangloff, Katherine Morales, Yohan Petetin
2021 J jnl
Structured Variational Bayesian Inference for Gaussian State-Space Models With Regime Switching.
IEEE Signal Process. Lett.
Yohan Petetin, Yazid Janati, François Desbouvries
2021 — conf
Variational Bayesian Inference for Pairwise Markov Models.
SSP
Katherine Morales, Yohan Petetin
2020 J jnl
Combining Federated and Active Learning for Communication-efficient Distributed Failure Prediction in Aeronautics.
CoRR
Nicolas Aussel, Sophie Chabridon, Yohan Petetin
2019 C conf
Comparing the Modeling Powers of RNN and HMM.
ICMLA
Achille Salaün, Yohan Petetin, François Desbouvries
2018 — conf
A Double Proposal Normalized Importance Sampling Estimator.
SSP
Roland Lamberti, Yohan Petetin, François Septier, François Desbouvries
2018 B conf
Improving Performances of Log Mining for Anomaly Prediction Through NLP-Based Log Parsing.
MASCOTS
Nicolas Aussel, Yohan Petetin, Sophie Chabridon
2018 J jnl
Semi-Independent Resampling for Particle Filtering.
IEEE Signal Process. Lett.
Roland Lamberti, Yohan Petetin, François Desbouvries, François Septier
2017 J jnl
Independent Resampling Sequential Monte Carlo Algorithms.
IEEE Trans. Signal Process.
Roland Lamberti, Yohan Petetin, François Desbouvries, François Septier
2017 C conf
Predictive Models of Hard Drive Failures Based on Operational Data.
ICMLA
Nicolas Aussel, Samuel Jaulin, Guillaume Gandon, Yohan Petetin, Eriza Fazli, Sophie Chabridon
2016 — conf
An improved SIR-based Sequential Monte Carlo algorithm.
SSP
Roland Lamberti, Yohan Petetin, François Septier, François Desbouvries
2016 Misc conf
Particle filters with independent resampling.
ICASSP
Roland Lamberti, Yohan Petetin, François Septier, François Desbouvries
2015 J jnl
Bayesian Conditional Monte Carlo Algorithms for Nonlinear Time-Series State Estimation.
IEEE Trans. Signal Process.
Yohan Petetin, François Desbouvries
2015 — conf
Deep neural networks for audio scene recognition.
EUSIPCO
Yohan Petetin, Cyrille Laroche, Aurélien Mayoue
2014 J jnl
A Class of Fast Exact Bayesian Filters in Dynamical Models With Jumps.
IEEE Trans. Signal Process.
Yohan Petetin, François Desbouvries
2014 — conf
Exact Bayesian estimation in constrained Triplet Markov Chains.
MLSP
Yohan Petetin, François Desbouvries
2014 J jnl
Filtrage statistique optimal rapide dans des systèmes linéaires à sauts non stationnaires.
Traitement du Signal
Noufel Abbassi, Stéphane Derrode, François Desbouvries, Yohan Petetin, Wojciech Pieczynski
2014 J jnl
Marginalized particle PHD filters for multiple object Bayesian filtering.
IEEE Trans. Aerosp. Electron. Syst.
Yohan Petetin, Mark R. Morelande, François Desbouvries
2013 J jnl
Bayesian Multi-Object Filtering for Pairwise Markov Chains.
IEEE Trans. Signal Process.
Yohan Petetin, François Desbouvries
2013 J jnl
Optimal SIR algorithm vs. fully adapted auxiliary particle filter: a non asymptotic analysis.
Stat. Comput.
Yohan Petetin, François Desbouvries
2012 — conf
A mixed GM/SMC implementation of the probability hypothesis density filter.
ISSPA
Yohan Petetin, François Desbouvries
2012 — conf
A semi-exact sequential Monte Carlo filtering algorithm in Hidden Markov Chains.
ISSPA
Yohan Petetin, François Desbouvries
2012 — conf
Further Rao-Blackwellizing an already Rao-Blackwellized algorithm for Jump Markov State Space Systems.
ISSPA
Yohan Petetin, François Desbouvries
2012 — conf
Marginalized PHD Filters for multi-target filtering.
ISSPA
Yohan Petetin, François Desbouvries
2012 — conf
Multi-object filtering for pairwise Markov chains.
ISSPA
Yohan Petetin, François Desbouvries
2011 J jnl
Direct, prediction- and smoothing-based Kalman and particle filter algorithms.
Signal Process.
François Desbouvries, Yohan Petetin, Boujemaa Ait-El-Fquih
2011 Misc conf
Optimal SIR algorithm vs. fully adapted auxiliary particle filter: A matter of conditional independence.
ICASSP
François Desbouvries, Yohan Petetin, Emmanuel Monfrini