LGMar 25, 2022
Supplemental Material: Lifelong Generative Modelling Using Dynamic Expansion Graph Model
arXiv:2203.13503v1Has Code
Originality Synthesis-oriented
AI Analysis
This is incremental work, offering supplementary details for a previously proposed method in generative modeling.
This paper provides supplemental material including additional visual and numerical results on challenging datasets, detailed proofs for the theoretical analysis framework, and source code for the lifelong generative modeling method.
In this article, we provide the appendix for Lifelong Generative Modelling Using Dynamic Expansion Graph Model. This appendix includes additional visual results as well as the numerical results on the challenging datasets. In addition, we also provide detailed proofs for the proposed theoretical analysis framework. The source code can be found in https://github.com/dtuzi123/Expansion-Graph-Model.