Exphormer: Sparse transformers for graphs H Shirzad, A Velingker, B Venkatachalam, DJ Sutherland, AK Sinop International Conference on Machine Learning, 31613-31632, 2023 | 100 | 2023 |
Evaluating graph generative models with contrastively learned features H Shirzad, K Hassani, DJ Sutherland Advances in Neural Information Processing Systems 35, 7783-7795, 2022 | 9 | 2022 |
TD-GEN: graph generation using tree decomposition H Shirzad, H Hajimirsadeghi, AH Abdi, G Mori International Conference on Artificial Intelligence and Statistics, 5518-5537, 2022 | 8* | 2022 |
A Theory for Compressibility of Graph Transformers for Transductive Learning H Shirzad, H Lin, A Velingker, B Venkatachalam, D Woodruff, ... arXiv preprint arXiv:2411.13028, 2024 | 1 | 2024 |
Even Sparser Graph Transformers H Shirzad, H Lin, B Venkatachalam, A Velingker, D Woodruff, ... The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 1 | 2024 |
Conditional diffusion models as self-supervised learning backbone for irregular time series H Shirzad, R Deng, H Zhao, F Tung ICLR 2024 Workshop on Learning from Time Series For Health, 2024 | 1 | 2024 |
Low-Width Approximations and Sparsification for Scaling Graph Transformers H Shirzad, B Venkatachalam, A Velingker, D Sutherland, D Woodruff NeurIPS 2023 Workshop: New Frontiers in Graph Learning, 2023 | | 2023 |
Scaling Graphically Structured Diffusion Models CD Weilbach, W Harvey, H Shirzad, F Wood ICML 2023 Workshop on Structured Probabilistic Inference {\&} Generative …, 2023 | | 2023 |
Graph generation using tree decomposition H Shirzad Simon Fraser University, 2021 | | 2021 |