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Yue Shen

DJI Innovations Inc

VAC2: Visual Analysis of Combined Causality in Event Sequences


Jun 11, 2022
Sujia Zhu, Yue Shen, Zihao Zhu, Wang Xia, Baofeng Chang, Ronghua Liang, Guodao Sun

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Model-free Learning of Regions of Attraction via Recurrent Sets


Apr 21, 2022
Yue Shen, Maxim Bichuch, Enrique Mallada

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Binary Neural Networks as a general-propose compute paradigm for on-device computer vision


Feb 08, 2022
Guhong Nie, Lirui Xiao, Menglong Zhu, Dongliang Chu, Yue Shen, Peng Li, Kang Yang, Li Du, Bo Chen

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* 13 pages, 3 figures 

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TNT: Target-driveN Trajectory Prediction


Aug 21, 2020
Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Congcong Li, Dragomir Anguelov

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Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing


Feb 27, 2020
Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi

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High-Order Paired-ASPP Networks for Semantic Segmenation


Feb 18, 2020
Yu Zhang, Xin Sun, Junyu Dong, Changrui Chen, Yue Shen

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Evolving Neural Networks through a Reverse Encoding Tree


Feb 03, 2020
Haoling Zhang, Chao-Han Huck Yang, Hector Zenil, Narsis A. Kiani, Yue Shen, Jesper N. Tegner

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* Submitted to IEEE WCCI-CEC 2020. Under review 

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Enabling real-time multi-messenger astrophysics discoveries with deep learning


Nov 26, 2019
E. A. Huerta, Gabrielle Allen, Igor Andreoni, Javier M. Antelis, Etienne Bachelet, Bruce Berriman, Federica Bianco, Rahul Biswas, Matias Carrasco, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Robert Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W. G. Johnson, Erik Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Marka, Kenton McHenry, Jonah Miller, Claudia Moreno, Mark Neubauer, Steve Oberlin, Alexander R. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Leo Singer, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

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* Nature Reviews Physics volume 1, pages 600-608 (2019) 
* Invited Expert Recommendation for Nature Reviews Physics. The art work produced by E. A. Huerta and Shawn Rosofsky for this article was used by Carl Conway to design the cover of the October 2019 issue of Nature Reviews Physics 

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Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era


Feb 01, 2019
Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Anushri Gupta, Roland Haas, E. A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, M. S. Neubauer, Steve Oberlin, Alexander R. Olivas Jr, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

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* 15 pages, no figures. White paper based on the "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at NCSA, October 17-19, 2018 http://www.ncsa.illinois.edu/Conferences/DeepLearningLSST/ 

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