… • We discuss current trends of deep graph generators in both techniques and applications
and suggest future research directions accordingly. We believe this article helps readers …

… key application areas of deep graph generation. Lastly, we highlight challenges and
opportunities in the future study of deep graph generation. We hope that our survey will be useful for …

… comparisons: This survey compares the performance of … Survey The remaining part of the
survey is organized as follows. In Sections 2 and 3, we provide the taxonomy of deep graph …

… advances in graph analysis techniques. In this survey, we comprehensively review the
different types of deep learning methods on graphs. We divide the existing methods into five …

… inception of configurable graph generators that reproduce real-world graph properties and …
In this survey, we provide a detailed overview of the state-of-the-art modern graph generators …

… However, no relatively systematic survey of scene graphs exists at present. To this end, this
survey conducts a comprehensive investigation of the current scene graph research. More …

… graph-structured data which is defined in non-Euclidean space with multi-modality. In this
survey, we formally formulate the problem of graph … in different deep graph learning problems. …

… In order to establish connections among different researches and ease the understanding
of them, in this paper, we survey recent work on deep GSL for robust representations. …

… of the existing general graph generators, including recently emerged deep learning-based …
As shown in the recent survey [11], existing graph generators can be classified into two …

… Unlike these surveys, we aim to provide a comprehensive overview of graph learning methods,
… parts of graph learning, such as network embedding and deep learning based network …