---2024---
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A Graph-based Representation Framework for Trajectory Recovery via Spatiotemporal Interval-Informed Seq2Seq.
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Counterfactual User Sequence Synthesis Augmented with Continuous Time Dynamic Preference Modeling for Sequential POI Recommendation.
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Exploring Urban Semantics: A Multimodal Model for POI Semantic Annotation with Street View Images and Place Names.
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Enhancing Fine-Grained Urban Flow Inference via Incremental Neural Operator.
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Full Bayesian Significance Testing for Neural Networks in Traffic Forecasting.
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KDDC: Knowledge-Driven Disentangled Causal Metric Learning for Pre-Travel Out-of-Town Recommendation.
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Learning Hierarchy-Enhanced POI Category Representations Using Disentangled Mobility Sequences.
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Multi-Modality Spatio-Temporal Forecasting via Self-Supervised Learning. https://arxiv.org/abs/2405.03255
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Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction. https://arxiv.org/abs/2406.16992
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Make Bricks with a Little Straw: Large-Scale Spatio-Temporal Graph Learning with Restricted GPU-Memory Capacity.
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Personalized Federated Learning for Cross-city Traffic Prediction.
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Reframing Spatial Reasoning Evaluation in Language Models: A Real-World Simulation Benchmark for Qualitative Reasoning. https://arxiv.org/abs/2405.15064
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Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting. https://arxiv.org/abs/2312.00516
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SaSDim:Self-Adaptive Noise Scaling Diffusion Model for Spatial Time Series Imputation. https://arxiv.org/abs/2309.01988
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Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning. https://arxiv.org/abs/2404.14073
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WeatherGNN: Exploiting Complicated Relationships in Numerical Weather Prediction Bias Correction. https://arxiv.org/abs/2310.05517
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X-Light: Cross-City Traffic Signal Control Using Transformer on Transformer as Meta Multi-Agent Reinforcement Learner. https://arxiv.org/abs/2404.12090
---2023---
1. CTW: Confident Time-Warping for Time-Series Label-Noise Learning. Peitian Ma, Zhen Liu, Junhao Zheng, Linghao Wang, Qianli Ma.
2. CVTP3D: Cross-view Trajectory Prediction Using Shared 3D Queries for Autonomous Driving. Zijian Song, Huikun Bi, Ruisi Zhang, Tianlu Mao, Zhaoqi Wang.
3. DeLELSTM: Decomposition-based Linear Explainable LSTM to Capture Instantaneous and Long-term Effects in Time Series. Chaoqun Wang, Yijun Li, Xiangqian Sun, Qi Wu, Dongdong Wang, Zhixiang Huang.
4. Distilling Universal and Joint Knowledge for Cross-Domain Model Compression on Time Series Data. Qing Xu, Min Wu, Xiaoli Li, Kezhi Mao, Zhenghua Chen.
5. GPLight: Grouped Multi-agent Reinforcement Learning for Large-scale Traffic Signal Control. Yilin Liu, Guiyang Luo, Quan Yuan, Jinglin Li, Lei Jin, Bo Chen, Rui Pan.
6. Inducing Stackelberg Equilibrium through Spatio-Temporal Sequential Decision-Making in Multi-Agent Reinforcement Learning. Bin Zhang, Lijuan Li, Zhiwei Xu, Dapeng Li, Guoliang Fan.
7. InitLight: Initial Model Generation for Traffic Signal Control Using Adversarial Inverse Reinforcement Learning. Yutong Ye, Yingbo Zhou, Jiepin Ding, Ting Wang, Mingsong Chen, Xiang Lian.
8. Latent Processes Identification From Multi-View Time Series. Zenan Huang, Haobo Wang, Junbo Zhao, Nenggan Zheng.
9. Learning Gaussian Mixture Representations for Tensor Time Series Forecasting. Jiewen Deng, Renhe Jiang, Jinliang Deng, Xuan Song.
10. Not Only Pairwise Relationships: Fine-Grained Relational Modeling for Multivariate Time Series Forecasting. Jinming Wu, Qi Qi, Jingyu Wang, Haifeng Sun, Zhikang Wu, Zirui Zhuang, Jianxin Liao.
11. Open Anomalous Trajectory Recognition via Probabilistic Metric Learning. Qiang Gao, Xiaohan Wang, Chaoran Liu, Goce Trajcevski, Li Huang, Fan Zhou.
12. pTSE: A Multi-model Ensemble Method for Probabilistic Time Series Forecasting. Yunyi Zhou, Zhixuan Chu, Yijia Ruan, Ge Jin, yuchen huang, Sheng Li.
13. Reinforcement Learning Approaches for Traffic Signal Control under Missing Data. hao mei, Junxian Li, Bin Shi, Hua Wei.
14. Self-Recover: Forecasting Block Maxima in Time Series from Predictors with Disparate Temporal Coverage using Self-Supervised Learning. Asadullah Hill Galib, Andrew McDonald, Pang-Ning Tan, Lifeng Luo.
15. SMARTformer: Semi-Autoregressive Transformer with Efficient Integrated Window Attention for Long Time Series Forecasting. Yiduo Li, Zhongwen Rao, Zhe Li, Shiyi Qi, Lujia Pan, Zenglin Xu.
16. Self-Recover: Forecasting Block Maxima in Time Series from Predictors with Disparate Temporal Coverage using Self-Supervised Learning. Asadullah Hill Galib, Andrew McDonald, Pang-Ning Tan, Lifeng Luo.
17. Towards an Integrated View of Semantic Annotation for POIs with Spatial and Textual Information. Dabin Zhang, Ronghui Xu, Weiming Huang, Kai Zhao, Meng Chen.
---2022---
1. A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification. IJCAI 2022.
2. Deciphering Environmental Air Pollution with Large Scale City Data. IJCAI 2022.
3. DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data. IJCAI 2022.
4. Experimental Comparison and Survey of Twelve Time Series Anomaly Detection Algorithms (Extended Abstract). IJCAI 2022.
5. FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting. IJCAI 2022.
6. GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning. IJCAI 2022.
7. Harnessing Fourier Isovists and Geodesic Interaction for Long-Term Crowd Flow Prediction. IJCAI 2022.
8. Long-term Spatio-Temporal Forecasting via Dynamic Multiple-Graph Attention. IJCAI 2022.
9. Modeling Spatio-temporal Neighbourhood for Personalized Point-of-interest Recommendation. IJCAI 2022.
10. MetaER-TTE: An Adaptive Meta-learning Model for En Route Travel Time Estimation. IJCAI 2022.
11. Memory Augmented State Space Model for Time Series Forecasting. IJCAI 2022.
12. Multi-Agent Reinforcement Learning for Traffic Signal Control through Universal Communication Method. IJCAI 2022.
13. Neural Contextual Anomaly Detection for Time Series. IJCAI 2022.
14. Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data. IJCAI 2022.
15. Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting. IJCAI 2022.
16. T-SMOTE: Temporal-oriented Synthetic Minority Oversampling Technique for Imbalanced Time Series Classification. IJCAI 2022.
17. Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting. IJCAI 2022.
18. TinyLight: Adaptive Traffic Signal Control on Devices with Extremely Limited Resources. IJCAI 2022.
19. When Transfer Learning Meets Cross-City Urban Flow Prediction: Spatio-Temporal Adaptation Matters. IJCAI 2022.
---2021--- 1. Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentation-Yang Li, Tong Chen, Yadan Luo, Hongzhi Yin, Zi Huang
2. Dynamic Lane Traffic Signal Control with Group Attention and Multi-Timescale Reinforcement Learning-Qize Jiang, Jingze Li, Weiwei Sun, Baihua Zheng
3. GraphReach: Position-Aware Graph Neural Network using Reachability Estimations-Sunil Nishad, Shubhangi Agarwal, Arnab Bhattacharya, Sayan Ranu
4. MFNP: A Meta-optimized Model for Few-shot Next POI Recommendation-Huimin Sun, Jiajie Xu, Kai Zheng, Pengpeng Zhao, Pingfu Chao, Xiaofang Zhou
5. Multimodal Transformer Networks for Pedestrian Trajectory Prediction-Ziyi Yin, Ruijin Liu, Zhiliang Xiong, Zejian Yuan
6. Modeling Trajectories with Neural Ordinary Differential Equations-Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, Roger Zimmermann
7. Multi-version Tensor Completion for Time-delayed Spatio-temporal Data-Cheng Qian, Nikos Kargas, Cao Xiao, Lucas Glass, Nicholas Sidiropoulos, Jimeng Sun
8. Predicting Traffic Congestion Evolution: A Deep Meta Learning Approach-Yidan Sun, Guiyuan Jiang, Siew Kei Lam, Peilan He
9. Residential Electric Load Forecasting via Attentive Transfer of Graph Neural Networks-Weixuan Lin, Di Wu
10. Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning-Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Liefeng Bo, Xiyue Zhang, Tianyi Chen
11. TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning-Xu Chen, Junshan Wang, Kunqing Xie
12. Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting-Qingyi Pan, Wenbo Hu, Ning Chen
13. Traffic Congestion Alleviation over Dynamic Road Networks: Continuous Optimal Route Combination for Trip Query Streams-Ke Li, Lisi Chen, Shuo Shang, Panos Kalnis, Bin Yao
14. Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video-Jie Wu, Wei Zhang, Guanbin Li, Wenhao Wu, Xiao Tan, Yingying Li, Errui Ding, Liang Lin
---2020---
A Spatial Missing Value Imputation Method for Multi-view Urban Statistical Data. Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Bei Chen, Xiangjun Dong. IJCAI 2020. [paper]
A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling. Jie Feng, Ziqian Lin, Tong Xia, Funing Sun, Diansheng Guo, Yong Li. IJCAI 2020. [paper]
Cross-Interaction Hierarchical Attention Networks for Urban Anomaly Prediction. Chao Huang, Chuxu Zhang, Peng Dai, Liefeng Bo. IJCAI 2020. [paper]
Enhancing Urban Flow Maps via Neural ODEs. Fan Zhou, Liang Li, Ting Zhong, Goce Trajcevski, Kunpeng Zhang, Jiahao Wang. IJCAI 2020. [paper]
LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks. Rongzhou Huang, Chuyin Huang, Yubao Liu, Genan Dai, Weiyang Kong. IJCAI 2020. [paper]
MaCAR: Urban Traffic Light Control via Active Multi-agent Communication and Action Rectification. Zhengxu Yu, Shuxian Liang, Long Wei, Zhongming Jin, Jianqiang Huang, Deng Cai, Xiaofei He, Xian-Sheng Hua. IJCAI 2020. [paper]
Multi-View Joint Graph Representation Learning for Urban Region Embedding. Mingyang Zhang, Tong Li, Yong Li, Pan Hui. IJCAI 2020. [paper]
Spatio-Temporal Change Detection Using Granger Sequence Pattern. Nat Pavasant, Masayuki Numao, Ken-ichi Fukui. IJCAI 2020. [paper]
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution. Sankalp Garg, Navodita Sharma, Woojeong Jin, Xiang Ren. IJCAI 2020. [paper]
Towards Alleviating Traffic Congestion: Optimal Route Planning for Massive-Scale Trips. Ke Li, Lisi Chen, Shuo Shang. IJCAI 2020. [paper]
Trajectory Similarity Learning with Auxiliary Supervision and Optimal Matching. Hanyuan Zhang, Xinyu Zhang, Qize Jiang, Baihua Zheng, Zhenbang Sun, Weiwei Sun, Changhu Wang. IJCAI 2020. [paper]
---2019---
AddGraph: Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN. Li Zheng, Zhenpeng Li, Jian Li, Zhao Li, Jun Gao. IJCAI 2019. [paper]
A Decomposition Approach for Urban Anomaly Detection Across Spatiotemporal Data. Mingyang Zhang, Tong Li, Hongzhi Shi, Yong Li , Pan Hui. IJCAI 2019. [paper]
Cross-City Transfer Learning for Deep Spatio-Temporal Prediction. Leye Wang, Xu Geng, Xiaojuan Ma, Feng Liu, Qiang Yang. IJCAI 2019. [paper]
GSTNet: Global Spatial-Temporal Network for Traffic Flow Prediction. Shen Fang, Qi Zhang, Gaofeng Meng, Shiming Xiang, Chunhong Pan. IJCAI 2019. [paper]
Graph WaveNet for Deep Spatial-Temporal Graph Modeling. Zonghan Wu, Guodong Long, Chengqi Zhang. IJCAI 2019. [paper]
Multi-Group Encoder-Decoder Networks to Fuse Heterogeneous Data for Next-Day Air Quality Prediction. Yawen Zhang, Qin Lv, Duanfeng Gao, Si Shen, Robert P Dick, Michael Hannigan, Qi Liu. IJCAI 2019. [paper]
Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs. Dongkuan Xu, Wei Cheng, Dongsheng Luo, Xiao Liu, Xiang Zhang. IJCAI 2019. [paper]
STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting. Lei Bai, Lina Yao, Salil S. Kanhere. IJCAI 2019. [paper]
Travel Time Estimation without Road Networks: An Urban Morphological Layout Representation Approach. Wuwei Lan, Yanyan Xu, Bin Zhao. IJCAI 2019. [paper]
---2018---
A Fast and Accurate Method for Estimating People Flow from Spatiotemporal Population Data. Yasunori Akagi, Takuya Nishimura , Takeshi Kurashima, Hiroyuki Toda. IJCAI 2018. [paper]
Exploiting Graph Regularized Multi-dimensional Hawkes Processes for Modeling Events with Spatio-temporal Characteristics. Yanchi Liu, Tan Yan, Haifeng Chen. IJCAI 2018. [paper]
Estimating Latent People Flow without Tracking Individuals. Tomoharu Iwata, Takeshi Kurashima, Hiroyuki Toda, Naonori Ueda. IJCAI 2018. [paper]
HST-LSTM: A Hierarchical Spatial-Temporal Long-Short Term Memory Network for Location Prediction. Dejiang Kong, Fei Wu. IJCAI 2018. [paper]
LC-RNN: A Deep Learning Model for Traffic Speed Prediction. Zhongjian Lv, Jiajie Xu, Kai Zheng, Hongzhi Yin, Pengpeng Zhao, Xiaofang Zhou. IJCAI 2018. [paper]
MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling. Jianpeng Xu, Xi Liu, Tyler Wilson, Pang-Ning Tan, Pouyan Hatami, Lifeng Luo. IJCAI 2018. [paper]
Predicting the Spatio-Temporal Evolution of Chronic Diseases in Population with Human Mobility Data. Yingzi Wang, Xiao Zhou, Anastasios Noulas, Cecilia Mascolo, Xing Xie, Enhong Chen. IJCAI 2018. [paper]
Representing Urban Functions through Zone Embedding with Human Mobility Patterns. Zijun Yao, Yanjie Fu, Bin Liu, Wangsu Hu, Hui Xiong. IJCAI 2018. [paper]
Spatio-Temporal Check-in Time Prediction with Recurrent Neural Network based Survival Analysis. Guolei Yang, Ying Cai, Chandan K. Reddy. IJCAI 2018. [paper]
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting. Bing Yu, Haoteng Yin, Zhanxing Zhu. IJCAI 2018. [paper]
Trajectory-User Linking via Variational AutoEncoder. Fan Zhou, Goce Trajcevski, Ting Zhong, Fengli Zhang. IJCAI 2018. [paper]
---2017---
Identifying Human Mobility via Trajectory Embeddings. Fan Zhou , Kunpeng Zhang, Goce Trajcevski, Xucheng Luo, Fengli Zhang. IJCAI 2017. [paper]
Understanding People Lifestyles: Construction of Urban Movement Knowledge Graph from GPS Trajectory. Nicholas Jing Yuan, Ruihua Song, Xing Xie, Qiang Ma. IJCAI 2017. [paper]
---2016---
Urban Water Quality Prediction Based on Multi-Task Multi-View Learning. Ye Liu, Yu Zheng, Yuxuan Liang, Shuming Liu, David S. Rosenblum. IJCAI 2016. [paper]