| Knowledge hypergraphs: Prediction beyond binary relations B Fatemi, P Taslakian, D Vazquez, D Poole International Joint Conferences on Artificial Intelligence (IJCAI) 2020, 2020 | 102* | 2020 |
| SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks B Fatemi, LE Asri, SM Kazemi Advances in Neural Information Processing Systems (NeurIPS) 2021, 2021 | 89 | 2021 |
| Improved knowledge graph embedding using background taxonomic information B Fatemi, S Ravanbakhsh, D Poole Proceedings of the AAAI conference on artificial intelligence 33 (01), 3526-3533, 2019 | 37 | 2019 |
| Structure learning for relational logistic regression: An ensemble approach N Ramanan, G Kunapuli, T Khot, B Fatemi, SM Kazemi, D Poole, ... Proceedings of the Sixteenth International Conference on Principles of …, 2018 | 16 | 2018 |
| A learning algorithm for relational logistic regression: Preliminary results B Fatemi, SM Kazemi, D Poole IJCAI Workshop on StarAI, 2016 | 12 | 2016 |
| Comparing aggregators for relational probabilistic models SM Kazemi, B Fatemi, A Kim, Z Peng, MR Tora, X Zeng, M Dirks, D Poole UAI Workshop on StarAI, 2017 | 9* | 2017 |
| A retrievable genetic algorithm for efficient solving of sudoku puzzles SM Kazemi, B Fatemi International Journal of Computer and Information Engineering 8 (5), 736-740, 2014 | 6 | 2014 |
| Knowledge hypergraph embedding meets relational algebra B Fatemi, P Taslakian, D Vazquez, D Poole Journal of Machine Learning Research 24 (105), 1-34, 2023 | 4 | 2023 |
| Record Linkage to Match Customer Names: A Probabilistic Approach B Fatemi, SM Kazemi, D Poole ICML Workshop on StarAI, 2018 | 4 | 2018 |
| Rating and generating Sudoku puzzles based on constraint satisfaction problems B Fatemi, SM Kazemi, N Mehrasa International Journal of Computer and Information Engineering 8 (10), 1816-1821, 2014 | 4 | 2014 |
| Talk like a graph: Encoding graphs for large language models B Fatemi, J Halcrow, B Perozzi arXiv preprint arXiv:2310.04560, 2023 | 3 | 2023 |
| Ugsl: A unified framework for benchmarking graph structure learning B Fatemi, S Abu-El-Haija, A Tsitsulin, M Kazemi, D Zelle, N Bulut, ... arXiv preprint arXiv:2308.10737, 2023 | 2 | 2023 |
| System and method for structure learning for graph neural networks B Fatemi, SM Kazemi, L El Asri US Patent App. 17/484,363, 2022 | 2 | 2022 |
| Submix: Learning to mix graph sampling heuristics S Abu-El-Haija, JV Dillon, B Fatemi, K Axiotis, N Bulut, J Gasteiger, ... Uncertainty in Artificial Intelligence, 1-10, 2023 | 1 | 2023 |
| Learning to Substitute Ingredients in Recipes B Fatemi, Q Duval, R Girdhar, M Drozdzal, A Romero-Soriano arXiv preprint arXiv:2302.07960, 2023 | 1 | 2023 |
| Finding a Record in a Database B Fatemi University of British Columbia, 2017 | 1 | 2017 |
| TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs PM Phothilimthana, S Abu-El-Haija, K Cao, B Fatemi, C Mendis, B Perozzi arXiv preprint arXiv:2308.13490, 2023 | | 2023 |
| 19th International Workshop on Mining and Learning with Graphs (MLG) N Shah, S Fakhraei, D Zheng, B Fatemi, L Akoglu Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | | 2023 |
| TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs P Mangpo Phothilimthana, S Abu-El-Haija, K Cao, B Fatemi, C Mendis, ... arXiv e-prints, arXiv: 2308.13490, 2023 | | 2023 |
| Geometric deep learning of particle motion by MAGIK B Fatemi, J Halcrow, K Jaqaman Nature Machine Intelligence 5 (5), 483-484, 2023 | | 2023 |
David PooleProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
