sigcomm

Menu

  • Home
  • Research
  • People
  • Open positions & theses
  • Publications
  • Teaching
  • Datasets and External Resources
  • Contact
Sigillo di Ateneo Sigillo di Ateneo

Applications of factor graph methods to filtering and smoothing for state space models

Sei qui: sigcomm > Applications of factor graph methods to filtering and smoothing for state space models

Our contributions to this research field concerns the development of novel Bayesian filtering and smoothing methods. All our methods are derived message passing algorithms over factor graphs.

Publications

  1. G. M. Vitetta, P. D. Viesti, E. Sirignano and F. Montorsi, “Multiple Bayesian Filtering as Message Passing,” in IEEE Transactions on Signal Processing, vol. 68, pp. 1002-1020, 2020, doi: 10.1109/TSP.2020.2965296.
  2. P. Di Viesti, G. M. Vitetta and E. Sirignano, “Double Bayesian Smoothing as Message Passing,” in IEEE Transactions on Signal Processing, vol. 67, no. 21, pp. 5495-5510, 1 Nov.1, 2019, doi: 10.1109/TSP.2019.2941064.
  3. G. M. Vitetta, E. Sirignano, P. D. Viesti, F. Montorsi and M. Sola, “Marginalized Particle Filtering and Related Filtering Techniques as Message Passing,” in IEEE Transactions on Signal Processing, vol. 67, no. 6, pp. 1522-1536, 15 March15, 2019, doi: 10.1109/TSP.2019.2893868.
  4. G. M. Vitetta, E. Sirignano and F. Montorsi, “Particle Smoothing for Conditionally Linear Gaussian Models as Message Passing Over Factor Graphs,” in IEEE Transactions on Signal Processing, vol. 66, no. 14, pp. 3633-3648, 1 July15, 2018, doi: 10.1109/TSP.2018.2835379.
© 2025 UNIMORE - Servizi Web - Privacy - Crediti