Obserwuj
Meng Qu
Meng Qu
Quebec AI Institute (Mila)
Zweryfikowany adres z umontreal.ca - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Line: Large-scale information network embedding
J Tang, M Qu, M Wang, M Zhang, J Yan, Q Mei
Proceedings of the 24th international conference on world wide web, 1067-1077, 2015
60662015
Pte: Predictive text embedding through large-scale heterogeneous text networks
J Tang, M Qu, Q Mei
Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015
9152015
Cotype: Joint extraction of typed entities and relations with knowledge bases
X Ren, Z Wu, W He, M Qu, CR Voss, H Ji, TF Abdelzaher, J Han
Proceedings of the 26th international conference on world wide web, 1015-1024, 2017
3262017
Gmnn: Graph markov neural networks
M Qu, Y Bengio, J Tang
International conference on machine learning, 5241-5250, 2019
3102019
Recurrent event network: Autoregressive structure inference over temporal knowledge graphs
W Jin, M Qu, X Jin, X Ren
arXiv preprint arXiv:1904.05530, 2019
2952019
Meta-path guided embedding for similarity search in large-scale heterogeneous information networks
J Shang, M Qu, J Liu, LM Kaplan, J Han, J Peng
arXiv preprint arXiv:1610.09769, 2016
1932016
An attention-based collaboration framework for multi-view network representation learning
M Qu, J Tang, J Shang, X Ren, M Zhang, J Han
Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017
1882017
Probabilistic logic neural networks for reasoning
M Qu, J Tang
Advances in neural information processing systems 32, 2019
1702019
Afet: Automatic fine-grained entity typing by hierarchical partial-label embedding
X Ren, W He, M Qu, L Huang, H Ji, J Han
Proceedings of the 2016 conference on empirical methods in natural language …, 2016
1642016
Label noise reduction in entity typing by heterogeneous partial-label embedding
X Ren, W He, M Qu, CR Voss, H Ji, J Han
Proceedings of the 22nd ACM SIGKDD international conference on Knowledge …, 2016
1582016
Graphmix: Improved training of gnns for semi-supervised learning
V Verma, M Qu, K Kawaguchi, A Lamb, Y Bengio, J Kannala, J Tang
Proceedings of the AAAI conference on artificial intelligence 35 (11), 10024 …, 2021
1512021
Rnnlogic: Learning logic rules for reasoning on knowledge graphs
M Qu, J Chen, LP Xhonneux, Y Bengio, J Tang
arXiv preprint arXiv:2010.04029, 2020
1472020
Graphvite: A high-performance cpu-gpu hybrid system for node embedding
Z Zhu, S Xu, J Tang, M Qu
The World Wide Web Conference, 2494-2504, 2019
1342019
Continuous graph neural networks
LP Xhonneux, M Qu, J Tang
International conference on machine learning, 10432-10441, 2020
1302020
Few-shot relation extraction via bayesian meta-learning on relation graphs
M Qu, T Gao, LP Xhonneux, J Tang
International conference on machine learning, 7867-7876, 2020
1152020
Proceedings of the 24th international conference on world wide web
J Tang, M Qu, M Wang, M Zhang, J Yan, Q Mei
Line: Large-scale information network embedding, 1067-1077, 2015
1132015
vgraph: A generative model for joint community detection and node representation learning
FY Sun, M Qu, J Hoffmann, CW Huang, J Tang
Advances in Neural Information Processing Systems 32, 2019
972019
Weakly-supervised relation extraction by pattern-enhanced embedding learning
M Qu, X Ren, Y Zhang, J Han
Proceedings of the 2018 World Wide Web Conference, 1257-1266, 2018
602018
Collaborative policy learning for open knowledge graph reasoning
C Fu, T Chen, M Qu, W Jin, X Ren
arXiv preprint arXiv:1909.00230, 2019
572019
Learning dual retrieval module for semi-supervised relation extraction
H Lin, J Yan, M Qu, X Ren
The world wide web conference, 1073-1083, 2019
572019
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