A flow model with a more-added coupling function
Xiang Ji, Xiaoming Ling, Hong‐Yan Chen, Xiaoyu Zhang, Zefei Dang · 2023
Unsupervised learning of probabilistic models is a core problem in machine learning. Under the foundation that the model of easy data modeling is good, the NICE model is proposed. A deep learning framework for complex high-dimensional density modeling is presented in NICE. In this paper, CovnFlow is added to NICE to construct a new coupled flow model. Although the basic model of NICE has been changed, the calculation of the Jacobi matrix is not much more complicated, and the newly proposed model will allow for a fuller fusion of information. So using this model to generate pictures will be more efficient and the effect will be better.