| Pytorch geometric temporal: Spatiotemporal signal processing with neural machine learning models B Rozemberczki, P Scherer, Y He, G Panagopoulos, A Riedel, ... Proceedings of the 30th ACM international conference on information …, 2021 | 232 | 2021 |
| Magnet: A neural network for directed graphs X Zhang, Y He, N Brugnone, M Perlmutter, M Hirn Advances in neural information processing systems 34, 27003-27015, 2021 | 131 | 2021 |
| Difformer: Scalable (graph) transformers induced by energy constrained diffusion Q Wu, C Yang, W Zhao, Y He, D Wipf, J Yan International Conference on Learning Representations (ICLR, Spotlight), 2023 | 87 | 2023 |
| SSSNET: semi-supervised signed network clustering Y He, G Reinert, S Wang, M Cucuringu Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 33 | 2022 |
| Msgnn: A spectral graph neural network based on a novel magnetic signed laplacian Y He, M Perlmutter, G Reinert, M Cucuringu Learning on Graphs Conference, 40: 1-40: 39, 2022 | 31 | 2022 |
| Gnnrank: Learning global rankings from pairwise comparisons via directed graph neural networks Y He, Q Gan, D Wipf, GD Reinert, J Yan, M Cucuringu international conference on machine learning, 8581-8612, 2022 | 31 | 2022 |
| Pytorch geometric signed directed: A software package on graph neural networks for signed and directed graphs Y He, X Zhang, J Huang, B Rozemberczki, M Cucuringu, G Reinert Learning on Graphs Conference, 12:1-12:27, 2024 | 27 | 2024 |
| Scan-flood fill (SCAFF): An efficient automatic precise region filling algorithm for complicated regions Y He, T Hu, D Zeng Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 24 | 2019 |
| DIGRAC: digraph clustering based on flow imbalance Y He, G Reinert, M Cucuringu Learning on Graphs Conference, 21: 1-21: 43, 2022 | 15* | 2022 |
| Ro-SOS: Metric Expression Network (MEnet) for Robust Salient Object Segmentation D Zeng, Y He, L Liu, Z Chen, J Huang, J Chen, J Paisley arXiv preprint arXiv:1805.05638, 2018 | 14 | 2018 |
| Pyramid graph neural network: A graph sampling and filtering approach for multi-scale disentangled representations H Geng, C Chen, Y He, G Zeng, Z Han, H Chai, J Yan Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 10 | 2023 |
| Gnns for node clustering in signed and directed networks Y He Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 7 | 2022 |
| Generalization Error of Graph Neural Networks in the Mean-field Regime G Aminian, Y He, G Reinert, Ł Szpruch, SN Cohen Proceedings of the 41st International Conference on Machine Learning 235 …, 2024 | 3 | 2024 |
| Robust Angular Synchronization via Directed Graph Neural Networks Y He, G Reinert, D Wipf, M Cucuringu International Conference on Learning Representations (ICLR 2024), 2023 | 3 | 2023 |
| Inferring Metabolic States from Single Cell Transcriptomic Data via Geometric Deep Learning HR Steach, S Viswanath, Y He, X Zhang, N Ivanova, M Hirn, M Perlmutter, ... 28th Annual International Conference on Research in Computational Molecular …, 2023 | 1 | 2023 |
| CEP3: Community Event Prediction with Neural Point Process on Graph X Wang, S Chen, Y He, M Wang, Q Gan, J Yan Learning on Graphs Conference, 39: 1-39: 17, 2022 | 1 | 2022 |
| Graph neural networks for network analysis Y He University of Oxford, 2024 | | 2024 |
| Data Study Group Final Report: Greenvest Solutions PS Eduardo Arnold,Jiaxin Chen, Ivan Croydon-Veleslavov, Anurag Deshpande ... https://doi.org/10.5281/zenodo.4534349, 2021 | | 2021 |
| MagNet: A Neural Network for Directed Graphs Supplementary Material X Zhang, Y He, N Brugnone, M Perlmutter, M Hirn | | |
Gesine ReinertProfessor of Statistics, University of Oxford Potvrđena adresa e-pošte na stats.ox.ac.uk
