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 |