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My Asilomar 2019 Schedule

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Technical Program

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MP5b: Advances in Bayesian Machine Learning (Invited)

Session Type: Oral
Time: Monday, November 4, 15:30 - 17:10
Location: Scripps
Session Chairs: Alec Koppel, US Army Research Laboratory and Brian Sadler, US Army Research Laboratory
 
  MP5b-1: DETECTING CAUSALITY USING DEEP GAUSSIAN PROCESSES
         Guanchao Feng; Stony Brook University
         J. Gerald Quirk; Stony Brook University Hospital
         Petar Djuric; Stony Brook University
 
  MP5b-2: COMPRESSED STREAMING IMPORTANCE SAMPLING FOR EFFICIENT REPRESENTATIONS OF LOCALIZATION DISTRIBUTIONS
         Amrit Singh Bedi; US Army Research Laboratory
         Alec Koppel; US Army Research Laboratory
         Brian Sadler; US Army Research Laboratory
         Victor Elvira; IMT Lille Douai
 
  MP5b-3: LEARNING GAUSSIAN PROCESSES WITH BAYESIAN POSTERIOR OPTIMIZATION
         Luiz F. O. Chamon; University of Pennsylvania
         Santiago Paternain; University of Pennsylvania
         Alejandro Ribeiro; University of Pennsylvania
 
  MP5b-4: THE LÉVY STATE SPACE MODEL
         Simon Godsill; University of Cambridge
         Marina Riabiz; University of Cambridge
         Ioannis Kontoyiannis; University of Cambridge