Deep graph generators: A survey F Faez, Y Ommi, MS Baghshah, HR Rabiee IEEE Access 9, 106675-106702, 2021 | 74 | 2021 |
SCGG: A deep structure-conditioned graph generative model F Faez, N Hashemi Dijujin, M Soleymani Baghshah, HR Rabiee Plos one 17 (11), e0277887, 2022 | 5 | 2022 |
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 | 4 | 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 | 3 | 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 | 2 | 2024 |
Logic Synthesis Optimization with Predictive Self-Supervision via Causal Transformers R Karimi, F Faez, Y Zhang, X Li, L Chen, M Yuan, M Biparva arXiv preprint arXiv:2409.10653, 2024 | | 2024 |
MTLSO: A Multi-Task Learning Approach for Logic Synthesis Optimization F Faez, R Karimi, Y Zhang, X Li, L Chen, M Yuan, M Biparva arXiv preprint arXiv:2409.06077, 2024 | | 2024 |