Technical Program

TMTSP_L2: Bayesian and Data Driven Methods

Session Type: Lecture
Time: Tuesday, August 30, 14:10 - 15:50
Location: Atlantic 1
Session Chair: Victor Elvira, University of Edinburgh
 
TMTSP_L2.1: A VERSATILE DISTRIBUTED MCMC ALGORITHM FOR LARGE SCALE INVERSE PROBLEMS
Pierre-Antoine Thouvenin, Pierre Chainais, Centrale Lille, France; Audrey Repetti, Heriot-Watt University, United Kingdom
 
TMTSP_L2.2: SAFE IMPORTANCE SAMPLING BASED ON PARTIAL POSTERIORS AND NEURAL VARIATIONAL APPROXIMATIONS
Fernando Llorente, Ernesto Curbelo, Pablo Olmos, David Delgado-Gómez, Universidad Carlos III de Madrid, Spain; Luca Martino, Universidad Rey Juan Carlo, Spain
 
TMTSP_L2.3: STATE-SPACE PARTITIONING SCHEMES IN MULTIPLE PARTICLE FILTERING FOR IMPROVED ACCURACY
Marija Iloska, Monica Bugallo, Stony Brook University, United States
 
TMTSP_L2.4: MIXTURE OF NOISES AND SAMPLING OF NON-LOG-CONCAVE POSTERIOR DISTRIBUTIONS
Pierre Palud, CRIStAL CNRS, France; Pierre Chainais, Pierre-Antoine Thouvenin, CRIStAL Centrale Lille, France; Franck Le Petit, Emeric Bron, Observatoire de Paris, France; Maxime Vono, Criteo, France
 
TMTSP_L2.5: APPLIANCE LOAD DISAGGREGATION BASED ON BAYESIAN SEQUENCE ESTIMATION USING IMPORTANCE SAMPLING
Venkata Pathuri-Bhuvana, Silicon Austria Labs and JKU LIT SAL eSPML Lab, Austria