Multi-head Variational Graph Autoencoder Constrained by Sum-product Networks

Author:

Xia Riting1ORCID,Zhang Yan1ORCID,Zhang Chunxu1ORCID,Liu Xueyan1ORCID,Yang Bo1ORCID

Affiliation:

1. Jilin University, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

ACM

Reference47 articles.

1. Najmeh Abiri and Mattias Ohlsson. 2019. Variational auto-encoders with Student’s t-prior. In ESANN. 415–420. Najmeh Abiri and Mattias Ohlsson. 2019. Variational auto-encoders with Student’s t-prior. In ESANN. 415–420.

2. Jinheon Baek Minki Kang and Sung Ju Hwang. 2021. Accurate Learning of Graph Representations with Graph Multiset Pooling. In ICLR. 1–22. Jinheon Baek Minki Kang and Sung Ju Hwang. 2021. Accurate Learning of Graph Representations with Graph Multiset Pooling. In ICLR. 1–22.

3. Jun Jin Choong Xin Liu and Tsuyoshi Murata. 2018. Learning Community Structure with Variational Autoencoder. In ICDM. 69–78. Jun Jin Choong Xin Liu and Tsuyoshi Murata. 2018. Learning Community Structure with Variational Autoencoder. In ICDM. 69–78.

4. Thilini Cooray and Ngai-Man Cheung. 2022. Graph-Wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning. In AAAI. 6420–6428. Thilini Cooray and Ngai-Man Cheung. 2022. Graph-Wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning. In AAAI. 6420–6428.

5. Robert Gens and Pedro Domingos. 2013. Learning the Structure of Sum-Product Networks. In ICML. 873–880. Robert Gens and Pedro Domingos. 2013. Learning the Structure of Sum-Product Networks. In ICML. 873–880.

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