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Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning
[ORAL] KDD 2019, Research Track (acceptance rate: 14.2%)
Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang#
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Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning
UrbanFM: Inferring Fine-Grained Urban Flows
KDD 2019, ADS Track (acceptance rate: 20.7%)
Yuxuan Liang, Kun Ouyang, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S. Rosenblum, Yu Zheng
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UrbanFM: Inferring Fine-Grained Urban Flows
DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
ACL 2019 (acceptance rate: 25.7%)
Huaishao Luo, Tianrui Li, Bing Liu, Junbo Zhang
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DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
DeepCrime: Attentive Hierarchical Recurrent Networks for Crime Prediction
As urban crimes (e.g., burglary and robbery) negatively impact our everyday life and must be addressed in a timely manner, predict- ing …
Chao Huang, Junbo Zhang, Yu Zheng, Nitesh V. Chawla
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Deep Distributed Fusion Network for Air Quality Prediction
KDD 2018, ADS Track (acceptance rate: 14.0%)
Xiuwen Yi, Junbo Zhang, Zhaoyuan Wang, Tianrui Li, Yu Zheng
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Deep Distributed Fusion Network for Air Quality Prediction
GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction
Numerous sensors have been deployed in different geospatial locations to continuously and cooperatively monitor the surrounding …
Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, Yu Zheng
Last updated on Feb 13, 2022
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GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction
Numerous sensors have been deployed in different geospatial locations to continuously and cooperatively monitor the surrounding …
Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, Yu Zheng
PDF Cite Code Project Most influential IJCAI papers
GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction
When Will You Arrive Estimating Travel Time Based on Deep Neural Networks
Estimating the travel time of any path (denoted by a sequence of connected road segments) in a city is of great importance to traffic …
Dong Wang, Junbo Zhang, Wei Cao, Jian Li, Yu Zheng
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Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
We proposed a deep-learning-based approach, called ST-ResNet, to collectively forecast the inflow and outflow of crowds in each and every region of a city.
Junbo Zhang, Yu Zheng, Dekang Qi
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Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
DNN-Based Prediction Model for Spatial-Temporal Data
Advances in location-acquisition and wireless communication technologies have led to wider availability of spatio-temporal (ST) data, …
Junbo Zhang, Yu Zheng, Dekang Qi, Ruiyuan Li, Xiuwen Yi
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