Deep graph generators: A survey F Faez, Y Ommi, MS Baghshah, HR Rabiee IEEE Access 9, 106675-106702, 2021 | 45 | 2021 |
Ccgg: A deep autoregressive model for class-conditional graph generation Y Ommi, M Yousefabadi, F Faez, A Sabour, M Soleymani Baghshah, ... Companion Proceedings of the Web Conference 2022, 1092-1098, 2022 | 3 | 2022 |
SCGG: A deep structure-conditioned graph generative model F Faez, N Hashemi Dijujin, M Soleymani Baghshah, HR Rabiee Plos one 17 (11), e0277887, 2022 | 1 | 2022 |
Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization M Biparva, R Karimi, F Faez, Y Zhang Temporal Graph Learning Workshop@ NeurIPS 2023, 2023 | | 2023 |
DMNP: A Deep Learning Approach for Missing Node Prediction in Partially Observed Graphs F Faez, AA Amiri, MS Baghshah, HR Rabiee 2022 IEEE/ACM International Conference on Advances in Social Networks …, 2022 | | 2022 |