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Ride-hailing demand prediction is an essential task in spatial-temporal data mining.
Long short-term memory
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A macroscopic taxi model for passenger demand, taxi utilization and level of services
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Gradient Flow in Recurrent Nets: the Difficulty of Learning Long-Term Dependencies
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A new model for learning in graph domains
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The Graph Neural Network Model
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ImageNet Classification with Deep Convolutional Neural Networks
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Predicting Taxi–Passenger Demand Using Streaming Data
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Bruna, J.; Zaremba, W.; Szlam, A.; and LeCun, Y. 2014 · 2014
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Sequence to Sequence Learning with Neural Networks
Sutskever, I.; Vinyals, O.; and Le, Q. V. 2014 · 2014
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Neural Machine Translation by Jointly Learning to Align and Translate
Bahdanau, D.; Cho, K.; and Bengio, Y. 2015 · 2015
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Where Are the Passengers?: A Grid-based Gaussian Mixture Model for Taxi Bookings
Chiang, M.-F.; Hoang, T.-A.; and Lim, E.-P. 2015 · 2015
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Adam: A Method for Stochastic Optimization
Kingma, D. P.; and Ba, J. 2015 · 2015
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Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
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XGBoost: A Scalable Tree Boosting System
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Long Short-Term Memory-Networks for Machine Reading
Cheng, J.; Dong, L.; and Lapata, M. 2016 · 2016
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Convolutional neural networks on graphs with fast localized spectral filtering
Defferrard, M.; Bresson, X.; and Vandergheynst, P. 2016 · 2016
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Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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Interpreting Traffic Dynamics Using Ubiquitous Urban Data
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A graph-based approach to measuring the efficiency of an urban taxi service system
Zhan, X.; Qian, X.; and Ukkusuri, S. V. 2016 · 2016
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Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
Zhang, J.; Zheng, Y.; and Qi, D. 2017 · 2017
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A taxi order dispatch model based on combinatorial optimization
Zhang, L.; Hu, T.; Min, Y.; Wu, G.; Zhang, J.; Feng, P.; Gong, P.; and Ye, J. 2017 · 2017
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Squeeze-and-excitation networks
Hu, J.; Shen, L.; and Sun, G. 2018 · 2018
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Graph Attention Networks
Veličković, P.; Cucurull, G.; Casanova, A.; Romero, A.; Lio, P.; and Bengio, Y. 2018 · 2018
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Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
Yao, H.; Wu, F.; Ke, J.; Tang, X.; Jia, Y.; Lu, S.; Gong, P.; Ye, J.; and Zhenhui, L. 2018 · 2018
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Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
Yu, B.; Yin, H.; and Zhu, Z. 2018 · 2018
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Semi-Supervised Classification with Graph Convolutional Networks
Kipf, T. N.; and Welling, M. 2017 · 2017
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A structured self-attentive sentence embedding
Lin, Z.; Feng, M.; Santos, C. N. d.; Yu, M.; Xiang, B.; Zhou, B.; and Bengio, Y. 2017 · 2017
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SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning
Long, C.; Zhang, H.; Xiao, J.; Nie, L.; Jian, S.; Wei, L.; and Chua, T. S. 2017 · 2017
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Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
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DeepSD: Supply-Demand Prediction for Online Car-Hailing Services Using Deep Neural Networks
Wang, D.; Cao, W.; Li, J.; and Ye, J. 2017 · 2017
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On Prediction of User Destination by Sub-Trajectory Understanding: A Deep Learning Based Approach
Zhao, J.; Xu, J.; Zhou, R.; Zhao, P.; Liu, C.; and Zhu, F. 2018 · 2018
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Spatiotemporal multi-graph convolution network for ride-hailing demand forecasting
Geng, X.; Li, Y.; Wang, L.; Zhang, L.; Yang, Q.; Ye, J.; and Liu, Y. 2019 · 2019
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PyTorch: An imperative style, high-performance deep learning library
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Taxi Origin-Destination Demand Prediction with Contextualized Spatial-Temporal Network
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Relational Action Forecasting
Sun, C.; Shrivastava, A.; Vondrick, C.; Sukthankar, R.; Murphy, K.; and Schmid, C. 2019 · 2019
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Learning convolutional neural networks for graphs
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Adaptive Seasonal Time Series Models for Forecasting Short-Term Traffic Flow
Shekhar, S.; and Williams, B. M. 2007 · 2024
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