Completed
Motivating Example
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Poisson Random Fields for Dynamic Feature Models
Automatically move to the next video in the Classroom when playback concludes
- 1 Introduction
- 2 Motivating Example
- 3 Poisson Random Field Development based on a population genetic model Sawyer and Hartl, 1992
- 4 Background: Indian Buffet Process
- 5 Background: Beta Process
- 6 The Wright-Fisher Model
- 7 The Wright-Fisher Diffusion
- 8 The Poisson Random Field
- 9 Poisson Random Field for Indian Buffet Processes
- 10 The WF-IBP model
- 11 MCMC inference
- 12 Simulated Data with Linear-Gaussian Observation Model
- 13 WF-IBP Topic Model
- 14 Comparing Dynamic vs Static Models (Simulated Data)
- 15 Comparing Dynamic vs Static Models (NIPS Data) Test-set perplexity
- 16 NIPS Topic Model
- 17 Concluding Remarks
- 18 References
