Y. Petetin

发表

A non asymptotical analysis of the optimal SIR algorithm vs. the fully adapted auxiliary particle filter

F. Desbouvries, E. Monfrini, Y. Petetin, 2011, 2011 IEEE Statistical Signal Processing Workshop (SSP).

A Class of Fast Exact Bayesian Filters in Dynamical Models With Jumps

F. Desbouvries, Y. Petetin, 2013, IEEE Transactions on Signal Processing.

Bayesian Conditional Monte Carlo Algorithms for Sequential Single and Multi-Object filtering

Y. Petetin, Franccois Desbouvries, 2012, 1210.5277.

Direct, prediction- and smoothing-based Kalman and particle filter algorithms

B. Ait‐El‐Fquih, F. Desbouvries, Y. Petetin, 2011, Signal Process..

Expressivity of Hidden Markov Chains vs. Recurrent Neural Networks From a System Theoretic Viewpoint

F. Desbouvries, Y. Petetin, Franccois Desbouvries, 2022, IEEE Transactions on Signal Processing.

Deep parameterizations of pairwise and triplet Markov models for unsupervised classification of sequential data

Y. Petetin, H. Gangloff, Katherine Morales, 2022, Comput. Stat. Data Anal..

Bayesian Conditional Monte Carlo Algorithms for Nonlinear Time-Series State Estimation

Yohan Petetin, François Desbouvries, F. Desbouvries, 2015, IEEE Transactions on Signal Processing.

Marginalized particle PHD filters for multiple object Bayesian filtering

Mark R. Morelande, Yohan Petetin, François Desbouvries, 2014, IEEE Transactions on Aerospace and Electronic Systems.

Bayesian Multi-Object Filtering for Pairwise Markov Chains

Yohan Petetin, François Desbouvries, F. Desbouvries, 2013, IEEE Transactions on Signal Processing.

A mixed GM/SMC implementation of the probability hypothesis density filter

Yohan Petetin, François Desbouvries, F. Desbouvries, 2012, 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA).

A tracker based on a CPHD filter approach for infrared applications

Branko Ristic, Daniel E. Clark, Dominique Maltese, 2011, Defense + Commercial Sensing.

Optimal SIR algorithm vs. fully adapted auxiliary particle filter: a non asymptotic analysis

Yohan Petetin, François Desbouvries, F. Desbouvries, 2012, Statistics and Computing.

A Double Proposal Normalized Importance Sampling Estimator

François Septier, Roland Lamberti, Yohan Petetin, 2018, 2018 IEEE Statistical Signal Processing Workshop (SSP).

Independent Resampling Sequential Monte Carlo Algorithms

François Septier, Roland Lamberti, Yohan Petetin, 2016, IEEE Transactions on Signal Processing.

A semi-exact sequential Monte Carlo filtering algorithm in Hidden Markov Chains

Yohan Petetin, François Desbouvries, F. Desbouvries, 2012, 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA).

A particle smoothing implementation of the fully-adapted auxiliary particle filter: An alternative to auxiliary particle filters

F. Desbouvries, Y. Petetin, 2011, 2011 IEEE Statistical Signal Processing Workshop (SSP).

Combining Federated and Active Learning for Communication-efficient Distributed Failure Prediction in Aeronautics pdf

Sophie Chabridon, Yohan Petetin, Nicolas Aussel, 2020, ArXiv.

Predictive Models of Hard Drive Failures Based on Operational Data

Sophie Chabridon, Yohan Petetin, Nicolas Aussel, 2017, 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA).

Deep neural networks for audio scene recognition

Aurélien Mayoue, Yohan Petetin, Cyrille Laroche, 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).

Comparing the Modeling Powers of RNN and HMM

Yohan Petetin, Achille Salaün, François Desbouvries, 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).

Improving Performances of Log Mining for Anomaly Prediction Through NLP-Based Log Parsing

Sophie Chabridon, Yohan Petetin, Nicolas Aussel, 2018, 2018 IEEE 26th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS).

Semi-Independent Resampling for Particle Filtering

Roland Lamberti, François Septier, Yohan Petetin, 2017, IEEE Signal Processing Letters.

Exact Bayesian estimation in constrained Triplet Markov Chains

Yohan Petetin, François Desbouvries, F. Desbouvries, 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Structured Variational Bayesian Inference for Gaussian State-Space Models With Regime Switching

Yohan Petetin, François Desbouvries, Yazid Janati, 2021, IEEE Signal Processing Letters.

A General Parametrization Framework for Pairwise Markov Models: An Application to Unsupervised Image Segmentation

Yohan Petetin, Hugo Gangloff, Katherine Morales, 2021, 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP).

Variational Bayesian Inference for Pairwise Markov Models

Y. Petetin, Katherine Morales, 2021, 2021 IEEE Statistical Signal Processing Workshop (SSP).