Poisson random fields for dynamic feature models
We present the Wright-Fisher Indian buffet process (WF-IBP), a probabilistic model for time-dependent data assumed to have been generated by an unknown number of latent features. This model is suitable as a prior in Bayesian nonparametric feature allocation models in which the features underlying th...
| Main Authors: | , , , |
|---|---|
| Format: | Journal article |
| Published: |
Journal of Machine Learning Research
2017
|