Fetching the paper…
Reading the bibliography…
Spatio-temporal prediction is a key type of tasks in urban computing, e.g., traffic flow and air quality.
Analysis of representations for domain adaptation
Shai Ben-David, John Blitzer, Koby Crammer, and Fernando Pereira · 2007
Earlier work this paper cites.
Learning bounds for domain adaptation
John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman · 2008
Earlier work this paper cites.
Domain adaptation: Learning bounds and algorithms
Yishay Mansour, Mehryar Mohri, and Afshin Rostamizadeh · 2009
Earlier work this paper cites.
A survey on transfer learning
Sinno Jialin Pan and Qiang Yang · 2010
Earlier work this paper cites.
Forecasting: principles and practice
Rob J Hyndman and George Athanasopoulos · 2014
Earlier work this paper cites.
Network in network
Min Lin, Qiang Chen, and Shuicheng Yan · 2014
Earlier work this paper cites.
Urban computing: concepts, methodologies, and applications
Yu Zheng, Licia Capra, Ouri Wolfson, and Hai Yang · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
Cited alongside, same era.
Convolutional lstm network: A machine learning approach for precipitation nowcasting
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Fccf: forecasting citywide crowd flows based on big data
Minh X Hoang, Yu Zheng, and Ambuj K Singh · 2016
Cited alongside, same era.
Transfer knowledge between cities
Ying Wei, Yu Zheng, and Qiang Yang · 2016
Cited alongside, same era.
Participatory cultural mapping based on collective behavior data in location-based social networks
Dingqi Yang, Daqing Zhang, and Bingqing Qu · 2016
Cited alongside, same era.
Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach
Jintao Ke, Hongyu Zheng, Hai Yang, and Xiqun Michael Chen · 2017
Later among the works it cites.
Ridesourcing car detection by transfer learning
Leye Wang, Xu Geng, Jintao Ke, Chen Peng, Xiaojuan Ma, Daqing Zhang, and Qiang Yang · 2017
Later among the works it cites.
Space-ta: Cost-effective task allocation exploiting intradata and interdata correlations in sparse crowdsensing
Leye Wang, Daqing Zhang, Dingqi Yang, Animesh Pathak, Chao Chen, Xiao Han, Haoyi Xiong, and Yasha Wang · 2017
Later among the works it cites.
Deep spatio-temporal residual networks for citywide crowd flows prediction
Junbo Zhang, Yu Zheng, and Dekang Qi · 2017
Later among the works it cites.
Citytransfer: Transferring inter- and intra-city knowledge for chain store site recommendation based on multi-source urban data
Bin Guo, Jing Li, Vincent W. Zheng, Zhu Wang, and Zhiwen Yu · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Dnn-based prediction model for spatio-temporal data
Junbo Zhang, Yu Zheng, Dekang Qi, Ruiyuan Li, and Xiuwen Yi · 2016
Cited alongside, same era.
Closest in time.
Deep multi-view spatial-temporal network for taxi demand prediction
Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang, Yitian Jia, Siyu Lu, Pinghua Gong, and Jieping Ye · 2018
Closest in time.