| Deep graph generators: A survey F Faez, Y Ommi, MS Baghshah, HR Rabiee IEEE Access 9, 106675-106702, 2021 | 54 | 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 | 2 | 2022 |
| 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 | 2 | 2022 |
| Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization M Biparva, R Karimi, F Faez, Y Zhang arXiv preprint arXiv:2402.05944, 2024 | 1 | 2024 |
| CCGG: A Deep Autoregressive Model for Class-Conditional Graph Generation M Yousefabadi, Y Ommi, F Faez, A Sabour, MS Baghshah, HR Rabiee arXiv e-prints, arXiv: 2110.03800, 2021 | | 2021 |
Mahdieh Soleymani BaghshahAssociate Professor, Computer Engineering Department, Sharif University of TechnologyVerified email at sharif.edu
