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Noise-Contrastive Estimation for Multivariate Point Processes


Nov 02, 2020
Hongyuan Mei, Tom Wan, Jason Eisner

* NeurIPS 2020 camera-ready 

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Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification


Jun 30, 2020
Hongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner

* ICML 2020 (near-camera-ready version) 

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Imputing Missing Events in Continuous-Time Event Streams


May 14, 2019
Hongyuan Mei, Guanghui Qin, Jason Eisner

* ICML 2019 camera-ready. The first version of this work appeared on OpenReview in September 2018 

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On the Idiosyncrasies of the Mandarin Chinese Classifier System


Apr 05, 2019
Shijia Liu, Hongyuan Mei, Adina Williams, Ryan Cotterell


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Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction


May 21, 2018
Hongyuan Mei, Sheng Zhang, Kevin Duh, Benjamin Van Durme

* *SEM 2018 camera-ready 

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The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process


Nov 21, 2017
Hongyuan Mei, Jason Eisner

* NIPS 2017 camera-ready. New experiments including intensity prediction evaluation, sensitivity to # of parameters, training speed analysis. Results updated to use final test data instead of devtest. Improved exposition, especially of continuous-time LSTM and thinning algorithm 

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Coherent Dialogue with Attention-based Language Models


Nov 21, 2016
Hongyuan Mei, Mohit Bansal, Matthew R. Walter

* To appear at AAAI 2017 

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What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment


Jan 08, 2016
Hongyuan Mei, Mohit Bansal, Matthew R. Walter


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Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences


Dec 17, 2015
Hongyuan Mei, Mohit Bansal, Matthew R. Walter

* To appear at AAAI 2016 (and an extended version of a NIPS 2015 Multimodal Machine Learning workshop paper) 

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Accurate Vision-based Vehicle Localization using Satellite Imagery


Oct 30, 2015
Hang Chu, Hongyuan Mei, Mohit Bansal, Matthew R. Walter

* 9 pages, 8 figures. Full version is submitted to ICRA 2016. Short version is to appear at NIPS 2015 Workshop on Transfer and Multi-Task Learning 

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