2016
NIPS
NeurIPS 2016
Poisson-Gamma dynamical systems
Abstract
This paper presents a dynamical system based on the Poisson-Gamma construction for sequentially observed multivariate count data. Inherent to the model is a novel Bayesian nonparametric prior that ties and shrinks parameters in a powerful way. We develop theory about the model's infinite limit and its steady-state. The model's inductive bias is demonstrated on a variety of real-world datasets where it is shown to learn interpretable structure and have superior predictive performance.
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Data Science & Analytics and Machine Learning
📈
Trend Setter
— Bayesian Optimization
🧭
Keyword Pioneer
— poisson-gamma model
🐣
Hot Topic Early Bird
— probabilistic modeling
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Bayesian & Probabilistic > Bayesian Learning
Data Science & Analytics > Methods > Time Series Analysis
Machine Learning > Bayesian & Probabilistic > Bayesian Inference
Machine Learning > Learning Types > Bayesian Optimization
Machine Learning > Bayesian & Probabilistic > Nonparametric Bayesian