| A heterogeneous graph neural model for cold-start recommendation S Liu, I Ounis, C Macdonald, Z Meng Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 116 | 2020 |
| Graph neural pre-training for recommendation with side information S Liu, Z Meng, C Macdonald, I Ounis ACM Transactions on Information Systems 41 (3), 1-28, 2023 | 53* | 2023 |
| Messages are never propagated alone: Collaborative hypergraph neural network for time-series forecasting N Yin, L Shen, H Xiong, B Gu, C Chen, XS Hua, S Liu, X Luo IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 30 | 2023 |
| An mlp-based algorithm for efficient contrastive graph recommendations S Liu, I Ounis, C Macdonald Proceedings of the 45th international ACM SIGIR conference on research and …, 2022 | 19 | 2022 |
| Beta-rec: Build, evaluate and tune automated recommender systems Z Meng, R McCreadie, C Macdonald, I Ounis, S Liu, Y Wu, X Wang, ... Proceedings of the 14th ACM Conference on Recommender Systems, 588-590, 2020 | 15 | 2020 |
| Sequence pre-training-based graph neural network for predicting lncRNA-miRNA associations Z Wang, S Liang, S Liu, Z Meng, J Wang, S Liang Briefings in Bioinformatics 24 (5), bbad317, 2023 | 11 | 2023 |
| Leveraging relational graph neural network for transductive model ensemble Z Hu, J Zhang, H Wang, S Liu, S Liang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 11 | 2023 |
| HMCDA: a novel method based on the heterogeneous graph neural network and metapath for circRNA-disease associations prediction S Liang, S Liu, J Song, Q Lin, S Zhao, S Li, J Li, S Liang, J Wang BMC bioinformatics 24 (1), 335, 2023 | 7 | 2023 |
| A Social-aware Gaussian Pre-trained model for effective cold-start recommendation S Liu, X Wang, C Macdonald, I Ounis Information Processing & Management 61 (2), 103601, 2024 | 6 | 2024 |
| Degree distribution based spiking graph networks for domain adaptation Y Wang, S Liu, M Wang, S Liang, N Yin arXiv preprint arXiv:2410.06883, 2024 | 4 | 2024 |
| Enhancing graph neural networks for recommender systems S Liu Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 4 | 2020 |
| PASCL: supervised contrastive learning with perturbative augmentation for particle decay reconstruction J Lu, S Liu, D Kobylianskii, E Dreyer, E Gross, S Liang Machine Learning: Science and Technology 5 (4), 045028, 2024 | 3 | 2024 |
| Heterogeneous biomedical entity representation learning for gene–disease association prediction Z Meng, S Liu, S Liang, B Jani, Z Meng Briefings in Bioinformatics 25 (5), bbae380, 2024 | 3 | 2024 |
| Social Regularisation in a BPR-based Venue Recommendation Systems S Liu, I Ounis, C Macdonald | 3 | 2019 |
| Dusego: Dual second-order equivariant graph ordinary differential equation Y Wang, N Yin, M Xiao, X Yi, S Liu, S Liang arXiv preprint arXiv:2411.10000, 2024 | 2 | 2024 |
| Enhancing graph neural networks via memorized global information R Zeng, J Fang, S Liu, Z Meng, S Liang ACM Transactions on the Web 18 (4), 1-34, 2024 | 2 | 2024 |
| BPP: a platform for automatic biochemical pathway prediction X Yi, S Liu, Y Wu, D McCloskey, Z Meng Briefings in Bioinformatics 25 (5), bbae355, 2024 | 2 | 2024 |
| Effective graph representation learning for ranking-based recommendation S Liu University of Glasgow, 2023 | 2 | 2023 |
| Factorised Neural Relational Inference for Particle Decay Reconstruction J Lu, S Liu, S Liang 2024 5th International Seminar on Artificial Intelligence, Networking and …, 2024 | 1 | 2024 |
| SGAC: A Graph Neural Network Framework for Imbalanced and Structure-Aware AMP Classification Y Wang, V Liang, N Yin, S Liu, E Segal arXiv preprint arXiv:2412.16276, 2024 | | 2024 |
Iadh OunisProfessor at the University of Glasgow, School of Computing ScienceAdresse e-mail validée de glasgow.ac.uk
