My CAMSAP 2019 Schedule

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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
         Jordi Vilà-Valls; Institut Supérieur de l’Aéronautique et de l’Espace, University of Toulouse
         Mónica F. Bugallo; Stony Brook University
         Joaquín Míguez; Universidad Carlos III de Madrid
         Pau Closas; Northeastern University
 
  WP3.2: A ROBUST HIGH-DIMENSIONAL BAYESIAN FILTER: THE STOCHASTIC GH-GENKF
         Francois Septier; Universite Bretagne Sud, Lab-STICC, UMR 6285, CNRS
         Tomoko Matsui; Institute of Statistical Mathematics
 
  WP3.3: ADAPTIVE IMPORTANCE SAMPLING SUPPORTED BY A VARIATIONAL AUTO-ENCODER
         Hechuan Wang; Stony Brook University
         Mónica F. Bugallo; Stony Brook University
         Petar Djurić; Stony Brook University
 
  WP3.4: RECURSIVE SHRINKAGE COVARIANCE LEARNING IN ADAPTIVE IMPORTANCE SAMPLING
         Yousef El-Laham; Stony Brook University
         Víctor Elvira; IMT Lille Douai
         Mónica F. Bugallo; Stony Brook University
 
  WP3.5: MULTILAYER MODELS OF RANDOM SEQUENCES: REPRESENTABILITY AND INFERENCE VIA NONLINEAR POPULATION MONTE CARLO
         Joaquin Míguez; Universidad Carlos III de Madrid
         Lucas Lacasa; Queen Mary University of London
         José A. Martínez-Ordoñez; Universidad Carlos III de Madrid
         Inés P. Mariño; Universidad Rey Juan Carlos
 
  WP3.6: PARTICLE FLOW PARTICLE FILTER USING GROMOV’S METHOD
         Soumyasundar Pal; McGill University
         Mark Coates; McGill University