Papers

2017

2016

2015

2014

bnpy: Reliable and scalable variational inference for Bayesian nonparametric models

Michael C. Hughes, Erik B. Sudderth

3rd NIPS Workshop on Probabilistic Programming

[paper PDF] [Python code: bnpy] [poster PDF]

Joint Modeling of Multiple Time Series via the Beta Process with Application to Motion Capture Segmentation.

Emily Fox, Michael C. Hughes, Erik B. Sudderth, Michael I. Jordan

Annals of Applied Statistics, Vol. 8(3), 2014.

[paper PDF] [supplement PDF] [Matlab code: NPBayesHMM]

2013

2012

Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data

Michael C. Hughes, Emily Fox, Erik B. Sudderth

Neural Information Processing Systems, 2012.

[paper PDF] [poster PDF] [supplement PDF]

The Nonparametric Metadata Dependent Relational Model

Dae Il Kim, Michael C. Hughes, Erik B. Sudderth

International Conference on Machine Learning, 2012.

[paper PDF] [poster PDF]

Nonparametric Discovery of Activity Patterns from Video Collections

Michael C. Hughes, Erik B. Sudderth

CVPR Workshop on Perceptual Organization in Computer Vision (POCV), 2012.

[paper PDF] [supplement ZIP] [Matlab code: NPBayesHMM]