| Constrained Graph Variational Autoencoders for Molecule Design Q Liu, M Allamanis, M Brockschmidt, AL Gaunt Neural Information Processing Systems, 2018 | 361 | 2018 |
| Quaternion Knowledge Graph Embedding S Zhang, Y Tay, L Yao, Q Liu Neural Information Processing Systems, 2019 | 322 | 2019 |
| Sentence-State LSTM for Text Representation Y Zhang, Q Liu, L Song 56th Annual Meeting of the Association for Computational Linguistics, 2018 | 223 | 2018 |
| Hyperbolic Graph Neural Networks Q Liu, M Nickel, D Kiela Neural Information Processing Systems, 2019 | 204 | 2019 |
| A survey on contextual embeddings Q Liu, MJ Kusner, P Blunsom arXiv preprint arXiv:2003.07278, 2020 | 114 | 2020 |
| Fusion of magnetic and visual sensors for indoor localization: Infrastructure-free and more effective Z Liu, L Zhang, Q Liu, Y Yin, L Cheng, R Zimmermann IEEE Transactions on Multimedia 19 (4), 874-888, 2016 | 108 | 2016 |
| EtherQL: a query layer for blockchain system Y Li, K Zheng, Y Yan, Q Liu, X Zhou Database Systems for Advanced Applications: 22nd International Conference …, 2017 | 102 | 2017 |
| Unsupervised Point Cloud Pre-Training via View-Point Occlusion, Completion H Wang, Q Liu, X Yue, J Lasenby, MJ Kusner International Conference on Computer Vision, 2020 | 92* | 2020 |
| Insertion-based decoding with automatically inferred generation order J Gu, Q Liu, K Cho Transactions of the Association for Computational Linguistics, 2019 | 88 | 2019 |
| Smart Contract Vulnerability Detection Using Graph Neural Networks Y Zhuang, Z Liu, P Qian, Q Liu, X Wang, Q He International Joint Conferences on Artificial Intelligence, 2020 | 83 | 2020 |
| Behavior pattern clustering in blockchain networks B Huang, Z Liu, J Chen, A Liu, Q Liu, Q He Multimedia Tools and Applications 76, 20099-20110, 2017 | 82 | 2017 |
| Towards natural and accurate future motion prediction of humans and animals Z Liu, S Wu, S Jin, Q Liu, S Lu, R Zimmermann, L Cheng Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 73 | 2019 |
| Learning domain representation for multi-domain sentiment classification Q Liu, Y Zhang, J Liu Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 44 | 2018 |
| Multi-task self-supervised learning for disfluency detection S Wang, W Che, Q Liu, P Qin, T Liu, WY Wang Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 9193-9200, 2020 | 39 | 2020 |
| Investigating pose representations and motion contexts modeling for 3D motion prediction Z Liu, S Wu, S Jin, S Ji, Q Liu, S Lu, L Cheng IEEE transactions on pattern analysis and machine intelligence 45 (1), 681-697, 2022 | 32 | 2022 |
| Counterfactual data augmentation for neural machine translation Q Liu, M Kusner, P Blunsom Proceedings of the 2021 Conference of the North American Chapter of the …, 2021 | 19 | 2021 |
| Pretraining the Noisy Channel Model for Task-Oriented Dialogue Q Liu, L Yu, L Rimell, P Blunsom Transactions of the Association for Computational Linguistics, 2021 | 17 | 2021 |
| Causal effect inference for structured treatments J Kaddour, Y Zhu, Q Liu, MJ Kusner, R Silva Advances in Neural Information Processing Systems 34, 24841-24854, 2021 | 15 | 2021 |
| Qalink: enriching text documents with relevant Q&A site contents Y Tang, W Huang, Q Liu, AKH Tung, X Wang, J Yang, B Zhang Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 15 | 2017 |
| Causal machine learning: A survey and open problems J Kaddour, A Lynch, Q Liu, MJ Kusner, R Silva arXiv preprint arXiv:2206.15475, 2022 | 11 | 2022 |
Matt J. KusnerAssociate Professor, University College LondonVerified email at ucl.ac.uk
