| A quantum Jensen–Shannon graph kernel for unattributed graphs L Bai, L Rossi, A Torsello, ER Hancock Pattern Recognition 48 (2), 344-355, 2015 | 111 | 2015 |
| Graph kernels from the jensen-shannon divergence L Bai, ER Hancock Journal of mathematical imaging and vision 47 (1), 60-69, 2013 | 109 | 2013 |
| Adaptive hash retrieval with kernel based similarity X Bai, C Yan, H Yang, L Bai, J Zhou, ER Hancock Pattern Recognition 75, 136-148, 2018 | 85 | 2018 |
| Learning backtrackless aligned-spatial graph convolutional networks for graph classification L Bai, L Cui, Y Jiao, L Rossi, ER Hancock IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (2), 783-798, 2020 | 79 | 2020 |
| BLoG: Bootstrapped graph representation learning with local and global regularization for recommendation M Li, L Zhang, L Cui, L Bai, Z Li, X Wu Pattern Recognition 144, 109874, 2023 | 78 | 2023 |
| Joint hypergraph learning and sparse regression for feature selection Z Zhang, L Bai, Y Liang, E Hancock Pattern Recognition 63, 291-309, 2017 | 78 | 2017 |
| Nonlocal similarity based nonnegative tucker decomposition for hyperspectral image denoising X Bai, F Xu, L Zhou, Y Xing, L Bai, J Zhou IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018 | 75 | 2018 |
| Quantum-based subgraph convolutional neural networks Z Zhang, D Chen, J Wang, L Bai, ER Hancock Pattern Recognition 88, 38-49, 2019 | 71 | 2019 |
| An aligned subtree kernel for weighted graphs L Bai, L Rossi, Z Zhang, E Hancock International Conference on Machine Learning, 30-39, 2015 | 61 | 2015 |
| Metalantis: A comprehensive underwater image enhancement framework H Wang, W Zhang, L Bai, P Ren IEEE Transactions on Geoscience and Remote Sensing, 2024 | 56 | 2024 |
| Fused lasso for feature selection using structural information L Cui, L Bai, Y Wang, SY Philip, ER Hancock Pattern Recognition 119, 108058, 2021 | 51 | 2021 |
| Depth-based complexity traces of graphs L Bai, ER Hancock Pattern Recognition 47 (3), 1172-1186, 2014 | 50 | 2014 |
| Attributed Graph Kernels Using the Jensen-Tsallis q-Differences L Bai, L Rossi, H Bunke, ER Hancock Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014 | 47 | 2014 |
| Entropic dynamic time warping kernels for co-evolving financial time series analysis L Bai, L Cui, Z Zhang, L Xu, Y Wang, ER Hancock IEEE Transactions on Neural Networks and Learning Systems 34 (4), 1808-1822, 2020 | 46 | 2020 |
| Internet financing credit risk evaluation using multiple structural interacting elastic net feature selection L Cui, L Bai, Y Wang, X Jin, ER Hancock Pattern recognition 114, 107835, 2021 | 44 | 2021 |
| Learning graph convolutional networks based on quantum vertex information propagation L Bai, Y Jiao, L Cui, L Rossi, Y Wang, SY Philip, ER Hancock IEEE Transactions on Knowledge and Data Engineering 35 (2), 1747-1760, 2021 | 42 | 2021 |
| Haqjsk: Hierarchical-aligned quantum jensen-shannon kernels for graph classification L Bai, L Cui, Y Wang, M Li, J Li, SY Philip, ER Hancock IEEE Transactions on Knowledge and Data Engineering, 2024 | 41 | 2024 |
| Fast depth-based subgraph kernels for unattributed graphs L Bai, ER Hancock Pattern Recognition 50, 233-245, 2016 | 41 | 2016 |
| Multimodal graph learning based on 3D Haar semi-tight framelet for student engagement prediction M Li, X Zhuang, L Bai, W Ding Information Fusion 105, 102224, 2024 | 39 | 2024 |
| Deep Rényi entropy graph kernel L Xu, L Bai, X Jiang, M Tan, D Zhang, B Luo Pattern Recognition 111, 107668, 2021 | 39 | 2021 |
Edwin HancockEmeritus Professor, Department of Computer Science, University of York, UKVerified email at cs.york.ac.uk
