Hanjun Dai
Hanjun Dai
Google Brain
Email verificata su gatech.edu - Home page
Citata da
Citata da
Learning Combinatorial Optimization Algorithms over Graphs
H Dai, EB Khalil, Y Zhang, B Dilkina, L Song
arXiv preprint arXiv:1704.01665, 2017
Discriminative embeddings of latent variable models for structured data
H Dai, B Dai, L Song
International Conference on Machine Learning, 2702-2711, 2016
Recurrent Marked Temporal Point Processes: Embedding Event History to Vector
N Du, H Dai, R Trivedi, U Upadhyay, M Gomez-Rodriguez, L Song
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016
Sequential click prediction for sponsored search with recurrent neural networks
Y Zhang, H Dai, C Xu, J Feng, T Wang, J Bian, B Wang, TY Liu
Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
A probabilistic model for learning multi-prototype word embeddings
F Tian, H Dai, J Bian, B Gao, R Zhang, E Chen, TY Liu
Proceedings of COLING 2014, the 25th International Conference on …, 2014
Adversarial Attack on Graph Structured Data
H Dai, H Li, T Tian, X Huang, L Wang, J Zhu, L Song
arXiv preprint arXiv:1806.02371, 2018
Syntax-Directed Variational Autoencoder for Structured Data
H Dai, Y Tian, B Dai, S Skiena, L Song
arXiv preprint arXiv:1802.08786, 2018
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
R Trivedi, H Dai, Y Wang, L Song
International Conference on Machine Learning, 3462-3471, 2017
Variational reasoning for question answering with knowledge graph
Y Zhang, H Dai, Z Kozareva, AJ Smola, L Song
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Material structure-property linkages using three-dimensional convolutional neural networks
A Cecen, H Dai, YC Yabansu, SR Kalidindi, L Song
Acta Materialia 146, 76-84, 2018
Deep Coevolutionary Network: Embedding User and Item Features for Recommendation
H Dai, Y Wang, R Trivedi, L Song
Provable Bayesian inference via particle mirror descent
B Dai, N He, H Dai, L Song
Artificial Intelligence and Statistics, 985-994, 2016
Learning Steady-States of Iterative Algorithms over Graphs
H Dai, Z Kozareva, B Dai, A Smola, L Song
International Conference on Machine Learning, 1114-1122, 2018
M-Statistic for Kernel Change-Point Detection
S Li, Y Xie, H Dai, L Song
Advances in Neural Information Processing Systems, 3348-3356, 2015
Learning loop invariants for program verification
X Si, H Dai, M Raghothaman, M Naik, L Song
Advances in Neural Information Processing Systems, 7751-7762, 2018
CompILE: Compositional Imitation Learning and Execution
T Kipf, Y Li, H Dai, V Zambaldi, A Sanchez-Gonzalez, E Grefenstette, ...
International Conference on Machine Learning, 3418-3428, 2019
Recurrent Hidden Semi-Markov Model
H Dai, B Dai, YM Zhang, S Li, L Song
KNET: A general framework for learning word embedding using morphological knowledge
Q Cui, B Gao, J Bian, S Qiu, H Dai, TY Liu
ACM Transactions on Information Systems (TOIS) 34 (1), 1-25, 2015
Sequence2Vec: A novel embedding approach for modeling transcription factor binding affinity landscape
H Dai, R Umarov, H Kuwahara, Y Li, L Song, X Gao
Bioinformatics, btx480, 2017
Learning a Meta-Solver for Syntax-Guided Program Synthesis
X Si, Y Yang, H Dai, M Naik, L Song
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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