Flexible and Hierarchical Prior for Bayesian Nonnegative Matrix Factorization

no code implementations • 23 May 2022 • Jun Lu, Xuanyu Ye

In this paper, we introduce a probabilistic model for learning nonnegative matrix factorization (NMF) that is commonly used for predicting missing values and finding hidden patterns in the data, in which the matrix factors are latent variables associated with each data dimension.

Bayesian Inference