Technical Program

WP3: Inference in High-Dimensional Spaces by Monte Carlo Methods

Session Type: Poster
Time: Wednesday, December 18, 16:00 - 17:20
Location: Terrace
Session Chair: Victor Elvira, IMT Lille Douai
 
WP3.1: SECOND ORDER SUBSPACE STATISTICS FOR ADAPTIVE STATE-SPACE PARTITIONING IN MULTIPLE PARTICLE FILTERING
Sara Pérez-Vieites, Universidad Carlos III de Madrid, Spain; Jordi Vilà-Valls, Institut Supérieur de l’Aéronautique et de l’Espace, University of Toulouse, France; Mónica F. Bugallo, Stony Brook University, United States; Joaquín Míguez, Universidad Carlos III de Madrid, Spain; Pau Closas, Northeastern University, United States
 
WP3.2: A ROBUST HIGH-DIMENSIONAL BAYESIAN FILTER: THE STOCHASTIC GH-GENKF
Francois Septier, Universite Bretagne Sud, Lab-STICC, UMR 6285, CNRS, France; Tomoko Matsui, Institute of Statistical Mathematics, Japan
 
WP3.3: ADAPTIVE IMPORTANCE SAMPLING SUPPORTED BY A VARIATIONAL AUTO-ENCODER
Hechuan Wang, Mónica F. Bugallo, Petar Djurić, Stony Brook University, United States
 
WP3.4: RECURSIVE SHRINKAGE COVARIANCE LEARNING IN ADAPTIVE IMPORTANCE SAMPLING
Yousef El-Laham, Stony Brook University, United States; Víctor Elvira, IMT Lille Douai, France; Mónica F. Bugallo, Stony Brook University, United States
 
WP3.5: MULTILAYER MODELS OF RANDOM SEQUENCES: REPRESENTABILITY AND INFERENCE VIA NONLINEAR POPULATION MONTE CARLO
Joaquin Míguez, Universidad Carlos III de Madrid, Spain; Lucas Lacasa, Queen Mary University of London, United Kingdom; José A. Martínez-Ordoñez, Universidad Carlos III de Madrid, Spain; Inés P. Mariño, Universidad Rey Juan Carlos, Spain
 
WP3.6: PARTICLE FLOW PARTICLE FILTER USING GROMOV’S METHOD
Soumyasundar Pal, Mark Coates, McGill University, Canada