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
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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 |
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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 |
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TMTSP_L2.3: STATE-SPACE PARTITIONING SCHEMES IN MULTIPLE PARTICLE FILTERING FOR IMPROVED ACCURACY |
Marija Iloska, Monica Bugallo, Stony Brook University, United States |
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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 |
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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 |
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