| N-gram graph: Simple unsupervised representation for graphs, with applications to molecules S Liu, MF Demirel, Y Liang Advances in neural information processing systems 32, 2019 | 170 | 2019 |
| Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials M Dai, MF Demirel, Y Liang, JM Hu npj Computational Materials 7 (1), 103, 2021 | 59 | 2021 |
| Graph neural network for predicting the effective properties of polycrystalline materials: A comprehensive analysis M Dai, MF Demirel, X Liu, Y Liang, JM Hu Computational Materials Science 230, 112461, 2023 | 8 | 2023 |
| An analysis of attentive walk-aggregating graph neural networks MF Demirel, S Liu, S Garg, Y Liang | 7 | 2021 |
| Attentive walk-aggregating graph neural networks MF Demirel, S Liu, S Garg, Z Shi, Y Liang Transactions on Machine Learning Research, 2022 | 6 | 2022 |
| Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials. npj Computational Materials 2021 7: 1 7 (1), 1–9 (2021) M Dai, MF Demirel, Y Liang, JM Hu DOI, 0 | 4 | |
| Analysis of sparse subspace clustering: Experiments and random projection MF Demirel, E Au-Yeung arXiv preprint arXiv:2204.00723, 2022 | 1 | 2022 |
| Author Correction: Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials M Dai, MF Demirel, Y Liang, JM Hu NPJ Computational Materials 8 (1), 2022 | | 2022 |
Shengchao LiuUC Berkeley & Caltech在 berkeley.edu 的电子邮件经过验证
