| Graph kernels from the jensen-shannon divergence L Bai, ER Hancock Journal of mathematical imaging and vision 47 (1), 60-69, 2013 | 90 | 2013 |
| A quantum jensen–shannon graph kernel for unattributed graphs L Bai, L Rossi, A Torsello, ER Hancock Pattern Recognition 48 (2), 344-355, 2015 | 81 | 2015 |
| Joint hypergraph learning and sparse regression for feature selection Z Zhang, L Bai, Y Liang, E Hancock Pattern Recognition 63, 291-309, 2017 | 54 | 2017 |
| 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 | 48 | 2018 |
| An aligned subtree kernel for weighted graphs L Bai, L Rossi, Z Zhang, E Hancock International Conference on Machine Learning, 30-39, 2015 | 48 | 2015 |
| Depth-based complexity traces of graphs L Bai, ER Hancock Pattern Recognition 47 (3), 1172-1186, 2014 | 43 | 2014 |
| Attributed Graph Kernels Using the Jensen-Tsallis q-Differences L Bai, L Rossi, H Bunke, ER Hancock Joint European Conference on Machine Learning and Knowledge Discovery in …, 2014 | 40 | 2014 |
| 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 | 35 | 2018 |
| Fast depth-based subgraph kernels for unattributed graphs L Bai, ER Hancock Pattern Recognition 50, 233-245, 2016 | 31 | 2016 |
| Quantum-based subgraph convolutional neural networks Z Zhang, D Chen, J Wang, L Bai, ER Hancock Pattern Recognition 88, 38-49, 2019 | 29 | 2019 |
| Quantum kernels for unattributed graphs using discrete-time quantum walks L Bai, L Rossi, L Cui, Z Zhang, P Ren, X Bai, E Hancock Pattern Recognition Letters 87, 96-103, 2017 | 27 | 2017 |
| Band weighting via maximizing interclass distance for hyperspectral image classification C Yan, X Bai, P Ren, L Bai, W Tang, J Zhou IEEE Geoscience and Remote Sensing Letters 13 (7), 922-925, 2016 | 21 | 2016 |
| A hypergraph kernel from isomorphism tests L Bai, P Ren, ER Hancock 2014 22nd International Conference on Pattern Recognition, 3880-3885, 2014 | 21 | 2014 |
| Depth-based hypergraph complexity traces from directed line graphs L Bai, F Escolano, ER Hancock Pattern Recognition 54, 229-240, 2016 | 18 | 2016 |
| A Graph Kernel based on Jensen-Shannon Representation L Bai, Z Zhang, ER Hancock International Joint Conference on Artificial Intelligence (IJCAI), 2015 | 18 | 2015 |
| A graph kernel from the depth-based representation L Bai, P Ren, X Bai, ER Hancock Joint IAPR International Workshops on Statistical Techniques in Pattern …, 2014 | 17 | 2014 |
| Depth-based subgraph convolutional auto-encoder for network representation learning Z Zhang, D Chen, Z Wang, H Li, L Bai, ER Hancock Pattern Recognition 90, 363-376, 2019 | 16 | 2019 |
| A quantum jensen-shannon graph kernel using the continuous-time quantum walk L Bai, ER Hancock, A Torsello, L Rossi International Workshop on Graph-Based Representations in Pattern Recognition …, 2013 | 15 | 2013 |
| A quantum-inspired similarity measure for the analysis of complete weighted graphs L Bai, L Rossi, L Cui, J Cheng, ER Hancock IEEE transactions on cybernetics 50 (3), 1264-1277, 2019 | 13 | 2019 |
| A hybrid reproducing graph kernel based on information entropy L Xu, X Jiang, L Bai, J Xiao, B Luo Pattern Recognition 73, 89-98, 2018 | 13 | 2018 |
Edwin HancockEmeritus Professor, Department of Computer Science, University of York, UKVerified email at cs.york.ac.uk
