T1.R2.4
LOCAL PARTICLE FILTERS: A UNIFYING FRAMEWORK AND NOVEL PARALLELIZABLE EXTENSIONS
Andrea Quintanilla, Víctor Elvira, University of Edinburgh, United Kingdom
Session:
T1.R2: Advances in Sequential Bayesian Inference Lecture
Track:
Special Sessions
Location:
Isabela II
Presentation Time:
Tue, 16 Dec, 11:20 - 11:40 AST (UTC -4)
Session Co-Chairs:
Petar Djuric, Stony Brook University and Joaquin Miguez, Universidad Carlos III de Madrid
Session T1.R2
T1.R2.1: BAYESIAN KOOPMAN TIME SERIES FORECASTING
Antonios Valkanas, Theodore Glavas, McGill University, Canada; Boris Oreshkin, Amazon, Canada; Mark Coates, McGill University, Canada
T1.R2.2: REVERSIBLE JUMP SMC
Matt Bright, Simon Maskell, University of Liverpool, United Kingdom
T1.R2.3: SEQUENTIAL BAYESIAN SIGNAL RECONSTRUCTION FOR UNLIMITED SAMPLING
Ralph McDougall, Simon Godsill, University of Cambridge, United Kingdom
T1.R2.4: LOCAL PARTICLE FILTERS: A UNIFYING FRAMEWORK AND NOVEL PARALLELIZABLE EXTENSIONS
Andrea Quintanilla, Víctor Elvira, University of Edinburgh, United Kingdom
T1.R2.5: Active–Subspace Particle Filtering for Efficient Inference in High-Dimensional State-Space Models
Petar M. Djuric, Nahid Shirdel Abdolmaleki, Anand Ravishankar, Stony Brook University, United States; Joaqun Miguez, Universidad Carlos III de Madrid, Spain
Contacts