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AAAI （2019-2024）

---2024---

  1. Cross-Domain Contrastive Learning for Time Series Clustering. https://ojs.aaai.org/index.php/AAAI/article/view/28740/29426

  2. CGS-Mask: Making Time Series Predictions Intuitive for All. https://arxiv.org/abs/2312.09513

  3. CUTS+: High-dimensional Causal Discovery from Irregular Time-series. https://arxiv.org/abs/2305.05890

  4. Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting. https://ojs.aaai.org/index.php/AAAI/article/view/29483/30795

  5. CI-STHPAN: Pre-Trained Attention Network for Stock Selection with Channel-Independent Spatio-Temporal Hypergraph. https://ojs.aaai.org/index.php/AAAI/article/download/28770/29478

  6. Diffusion Language-Shapelets for Semisupervised Time-series Classification. https://ojs.aaai.org/index.php/AAAI/article/download/29317/30486

  7. Energy-efficient Streaming Time Series Classification with Attentive Power Iteration. https://ojs.aaai.org/index.php/AAAI/article/view/29151/30177

  8. Earthfarsser: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model. https://arxiv.org/abs/2312.08403

  9. Fully-Connected Spatial-Temporal Graph for Multivariate Time Series Data. https://arxiv.org/abs/2309.05305

  10. Graph-Aware Contrasting for Multivariate Time-Series Classification. https://arxiv.org/abs/2309.05202v3

  11. GraFITi: Graphs for Forecasting Irregularly Sampled Time Series. https://arxiv.org/abs/2305.12932

  12. HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting. https://ojs.aaai.org/index.php/AAAI/article/download/29155/30185

  13. Hawkes-enhanced Spatial-Temporal Hypergraph Contrastive Learning based on Criminal Correlations. https://ojs.aaai.org/index.php/AAAI/article/download/28719/29390

  14. IVP-VAE: Modeling EHR Time Series with Initial Value Problem Solvers. https://arxiv.org/abs/2305.06741

  15. KGTS: Contrastive Trajectory Similarity Learning over Prompt Knowledge Graph Embedding. https://ojs.aaai.org/index.php/AAAI/article/download/28672/29305

  16. Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series Forecasting. https://arxiv.org/abs/2312.08763

  17. Latent Diffusion Transformer for Probabilistic Time Series Forecasting. https://ojs.aaai.org/index.php/AAAI/article/download/29085/30053

  18. Learning Time Slot Preferences via Mobility Tree for Next POI Recommendation. https://ojs.aaai.org/index.php/AAAI/article/view/28697/29350

  19. ModWaveMLP: MLP-based Mode Decomposition and Wavelet Denoising Model to Defeat Complex Structures in Traffic Forecasting. https://ojs.aaai.org/index.php/AAAI/article/view/28753/29449

  20. MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting. https://arxiv.org/abs/2401.00423

  21. Prompt to transfer: Sim-to-real Transfer for Traffic Signal Control with Prompt Learning. https://arxiv.org/abs/2308.14284

  22. SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation. https://arxiv.org/abs/2312.05790

  23. Spatial-Temporal Interplay in Human Mobility: A Hierarchical Reinforcement Learning Approach with Hypergraph Representation. https://arxiv.org/abs/2312.15717

  24. Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting. https://ojs.aaai.org/index.php/AAAI/article/download/28707/29368

  25. Successive POI Recommendation via Brain-inspired Spatiotemporal Aware Representation. https://ojs.aaai.org/index.php/AAAI/article/view/27813/27657

  26. TimesURL: Self-supervised Contrastive Learning for Universal Time Series Representation Learning. https://arxiv.org/abs/2312.15709

  27. Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective. https://ojs.aaai.org/index.php/AAAI/article/download/28759/29459

  28. U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting. https://arxiv.org/abs/2401.02236

  29. Urban Region Embedding via Multi-View Contrastive Prediction. https://ojs.aaai.org/index.php/AAAI/article/view/28718/29388

  30. When Model Meets New Normals: Test-time Adaptation for Unsupervised Time-series Anomaly Detection. https://arxiv.org/abs/2312.11976

---2023---

1. Continuous Trajectory Generation Based on Two-Stage GAN. Wenjun Jiang, Wayne Xin Zhao, Jingyuan Wang, Jiawei Jiang. AAAI 2023. [paper]

2. PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction. Jiawei Jiang, Chengkai Han, Wayne Xin Zhao, Jingyuan Wang. AAAI 2023. [paper]

3. Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction. Jiahao Ji, Jingyuan Wang, Chao Huang, Junjie Wu, Boren Xu, Zhenhe Wu, Junbo Zhang, Yu Zheng. AAAI 2023. [paper]

...

---2022---

1. Accurate and Scalable Gaussian Processes for Fine-Grained Air Quality Inference. Zeel B Patel, Palak Purohit, Harsh Patel, Shivam Sahni, Nipun Batra. AAAI 2022. [paper]

2. Bayesian Optimisation for Active Monitoring of Air Pollution. Sigrid Passano Hellan, Christopher G. Lucas, Nigel H. Goddard. AAAI 2022. [paper]

3. Complementary Attention Gated Network for Pedestrian Trajectory Prediction. Jinghai Duan, Le Wang, Chengjiang Long, Sanping Zhou, Fang Zheng, Liushuai Shi, Gang Hua. AAAI 2022. [paper]

4. Conditional Local Convolution for Spatio-Temporal Meteorological Forecasting. Haitao Lin, Zhangyang Gao, Yongjie Xu, Lirong Wu, Ling Li, Stan Z. Li. AAAI 2022. [paper]

5. CATN: Cross Attentive Tree-Aware Network for Multivariate Time Series Forecasting. Hui He, Qi Zhang, Simeng Bai, Kun Yi, Zhendong Niu. AAAI 2022. [paper]

6. Conditional Loss and Deep Euler Scheme for Time Series Generation. Carl Remlinger, Joseph Mikael, Romuald Elie. AAAI 2022. [paper]

7. CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting. Lijing Wang, Aniruddha Adiga, Jiangzhuo Chen, Adam Sadilek, Srinivasan Venkatramanan, Madhav Marathe. AAAI 2022. [paper]

8. Disentangled Spatiotemporal Graph Generative Model. Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Zhao Liang. AAAI 2022. [paper]

9. DeepGPD: A Deep Learning Approach for Modeling Geospatio-Temporal Extreme Events. Tyler Wilson, Pang-Ning Tan, Lifeng Luo. AAAI 2022. [paper]

10. Event-Aware Multimodal Mobility Nowcasting. Zhaonan Wang, Renhe Jiang, Hao Xue, Flora D. Salim, Xuan Song, Ryosuke Shibasaki. AAAI 2022. [paper]

11. Graph Neural Controlled Differential Equations for Traffic Forecasting. Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, Noseong Park. AAAI 2022. [paper] [code]

12. HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting. Chenyu Wang, Zongyu Lin, Xiaochen Yang, Jiao Sun, Mingxuan Yue, Cyrus Shahabi. AAAI 2022. [paper]

13. I-SEA: Importance Sampling and Expected Alignment-Based Deep Distance Metric Learning for Time Series Analysis and Embedding. Sirisha Rambhatla, Zhengping Che, Yan Liu. AAAI 2022. [paper]

14. Learning and Dynamical Models for Sub-Seasonal Climate Forecasting: Comparison and Collaboration. Sijie He, Xinyan Li, Laurie Trenary, Benjamin A. Cash, Timothy DelSole, Arindam Banerjee. AAAI 2022. [paper] [code]

15. Machine-Learned Prediction Equilibrium for Dynamic Traffic Assignment. Lukas Graf, Tobias Harks, Kostas Kollias, Michael Markl. AAAI 2022. [paper] [code]

16. Multi-Type Urban Crime Prediction. Xiangyu Zhao, Wenqi Fan, Hui Liu, Jiliang Tang. AAAI 2022. [paper]

17. Real-Time Driver-Request Assignment in Ridesourcing. Hao Wang, Xiaohui Bei. AAAI 2022. [paper]

18. Reinforcement Learning based Dynamic Model Combination for Time Series Forecasting. Yuwei Fu, Di Wu, Benoit Boulet. AAAI 2022. [paper]

19. STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction. Jiahao Ji, Jingyuan Wang, Zhe Jiang, Jiawei Jiang, Hu Zhang. AAAI 2022. [paper]

20. Social Interpretable Tree for Pedestrian Trajectory Prediction. Liushuai Shi, Le Wang, Chengjiang Long, Sanping Zhou, Fang Zheng, Nanning Zheng, Gang Hua. AAAI 2022. [paper]

21. SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss. Konstantin Klemmer, Tianlin Xu, Beatrice Acciaio, Daniel B. Neill. AAAI 2022. [paper]

22. Towards a Rigorous Evaluation of Time-Series Anomaly Detection. Siwon Kim, Kukjin Choi, Hyun-Soo Choi, Byunghan Lee, Sungroh Yoon. AAAI 2022. [paper]

23. TS2Vec: Towards Universal Representation of Time Series. Zhihan Yue, Yujing Wang, Juanyong Duan, Tianmeng Yang, Congrui Huang, Yunhai Tong, Bixiong Xu. AAAI 2022. [paper] [code]

---2021---

1. Attentive Neural Point Processes for Event Forecasting. Yulong Gu. AAAI 2021. [paper]

2. A Multi-Step-Ahead Markov Conditional Forward Model with Cube Perturbations for Extreme Weather Forecasting. Chia-Yuan Chang, Cheng-Wei Lu, Chuan-Ju Wang. AAAI 2021. [paper]

3. AttnMove: History Enhanced Trajectory Recovery via Attentional Network. Tong Xia, Jie Feng, Yunhan Qi, Fengli Xu, Yong Li, Diansheng Guo, Funing Sun. AAAI 2021. [paper]

4. Correlative Channel-Aware Fusion for Multi-View Time Series Classification. Yue Bai, Lichen Wang, Zhiqiang Tao, Sheng Li, Yun Fu. AAAI 2021. [paper]

5. Coupled Layer-Wise Graph Convolution for Transportation Demand Prediction. Junchen Ye, Leilei Sun, Bowen Du, Yanjie Fu, Hui Xiong. AAAI 2021.[paper]

6. CARPe Posterum: A Convolutional Approach for Real-Time Pedestrian Path Prediction. Matias Mendieta, Hamed Tabkhi. AAAI 2021. [paper]

7. Capturing Uncertainty in Unsupervised GPS Trajectory Segmentation Using Bayesian Deep Learning. Christos Markos, James Yu, Richard Yi Da Xu. AAAI 2021. [paper]

8. Community-Aware Multi-Task Transportation Demand Prediction. Hao Liu, Qiyu Wu, Fuzhen Zhuang, Xinjiang Lu, Dejing Dou, Hui Xiong. AAAI 2021. [paper]

9. Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting. Amirreza Farnoosh, Bahar Azari, Sarah Ostadabbas. AAAI 2021. [paper]

10. Dynamic Gaussian Mixture Based Deep Generative Model for Robust Forecasting on Sparse Multivariate Time Series. Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B Davidson. AAAI 2021. [paper]

11. Disentangled Multi-Relational Graph Convolutional Network for Pedestrian Trajectory Prediction. Inhwan Bae, Hae-Gon Jeon. AAAI 2021. [paper]

12. FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting. Boris N. Oreshkin, Arezou Amini, Lucy Coyle, Mark Coates. AAAI 2021. [paper]

13. GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting. Beibei Wang, Youfang Lin, Shengnan Guo, Huaiyu Wan. AAAI 2021.[paper]

14. Graph Neural Network-Based Anomaly Detection in Multivariate Time Series. Ailin Deng, Bryan Hooi. AAAI 2021. [paper]

15. Generative Semi-Supervised Learning for Multivariate Time Series Imputation. Xiaoye Miao, Yangyang Wu, Jun Wang, Yunjun Gao, Xudong Mao, Jianwei Yin. AAAI 2021. [paper]

16. Hierarchical Graph Convolution Network for Traffic Forecasting. Kan Guo, Yongli Hu, Yanfeng Sun, Sean Qian, Junbin Gao, Baocai Yin. AAAI 2021. [paper]

17. Hierarchically and Cooperatively Learning Traffic Signal Control. Bingyu Xu, Yaowei Wang, Zhaozhi Wang, Huizhu Jia, Zongqing Lu. AAAI 2021. [paper]

18. Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting. Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, Wancai Zhang. AAAI 2021. [paper]

19. Joint-Label Learning by Dual Augmentation for Time Series Classification. Qianli Ma, Zhenjing Zheng, Jiawei Zheng, Sen Li, Wanqing Zhuang, Garrison Cottrell. AAAI 2021. [paper]

20. Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks. Jindong Han, Hao Liu, Hengshu Zhu, Hui Xiong, Dejing Dou. AAAI 2021. [paper]

21. Learnable Dynamic Temporal Pooling for Time Series Classification. Dongha Lee, Seonghyeon Lee, Hwanjo Yu. AAAI 2021. [paper]

22. Learning Representations for Incomplete Time Series Clustering. Qianli Ma, Chuxin Chen, Sen Li, Garrison Cottrell. AAAI 2021. [paper]

23. Learning Precise Temporal Point Event Detection with Misaligned Labels. Julien Schroeter, Kirill Sidorov, David Marshal. AAAI 2021. [paper]

24. Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction. Qiang Zhou, Jingjing Gu, Xinjiang Lu, Fuzhen Zhuang, Yanchao Zhao, Qiuhong Wang, Xiao Zhang. AAAI 2021. [paper]

25. Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting. Boris N. Oreshkin, Dmitri Carpov, Chapados Nicolas, Yoshua Bengio. AAAI 2021. [paper]

26. Multi-Layer Networks for Ensemble Precipitation Forecasts Postprocessing. Fengyang Xu, Guanbin Li, Yunfei Du, Zhiguang Chen, Yutong Lu. AAAI 2021. [paper]

27. Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service. Amutheezan Sivagnanam, Afiya Ayman, Michael Wilbur, Philip Pugliese, Abhishek Dubey, Aron Laszka. AAAI 2021. [paper]

28. Out-of-Town Recommendation with Travel Intention Modeling. Haoran Xin, Xinjiang Lu, Tong Xu, Hao Liu, Jingjing Gu, Dejing Dou, Hui Xiong. AAAI 2021.[paper]

29. Outlier Impact Characterization for Time Series Data. Jianbo Li, Lecheng Zheng, Yada Zhu, Jingrui He. AAAI 2021. [paper]

30. Pre-Training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction. Yan Lin, Huaiyu Wan, Shengnan Guo, Youfang Lin. AAAI 2021. [paper]

31. Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed by Second-Order Traffic Models. Rongye Shi, Zhaobin Mo, Xuan Di. AAAI 2021. [paper]

32. PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation. Minseok Kim, Hwanjun Song, Doyoung Kim, Kijung Shin, Jae-Gil Lee. AAAI 2021. [paper]

33. Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning. Huiling Qin, Songyu Ke, Xiaodu Yang, Haoran Xu, Xianyuan Zhan, Yu Zheng. AAAI 2021. [paper]

34. Reinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspective. Dongjie Wang, Pengyang Wang, Kunpeng Liu, Yuanchun Zhou, Charles E Hughes, Yanjie Fu. AAAI 2021. [paper]

35. Second Order Techniques for Learning Time-Series with Structural Breaks. Takayuki Osogami. AAAI 2021. [paper]

36. ShapeNet: A Shapelet-Neural Network Approach for Multivariate Time Series Classification. Guozhong Li, Byron Choi, Jianliang Xu, Sourav S Bhowmick, Kwok-Pan Chun, Grace Lai-Hung Wong. AAAI 2021. [paper]

37. Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting. Mengzhang Li, Zhanxing Zhu. AAAI 2021. [paper]

38. Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances. Sijie He, Xinyan Li, Timothy DelSole, Pradeep Ravikumar, Arindam Banerjee. AAAI 2021. [paper]

39. Traffic Flow Prediction with Vehicle Trajectories. Mingqian Li, Panrong Tong, Mo Li, Zhongming Jin, Jianqiang Huang, Xian-Sheng Hua. AAAI 2021. [paper]

40. Temporal Latent Autoencoder: A Method for Probabilistic Multivariate Time Series Forecasting. Nam Nguyen, Brian Quanz. AAAI 2021. [paper]

41. Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision. Rongqin Liang, Yuanman Li, Xia Li, Yi Tang, Jiantao Zhou, Wenbin Zou. AAAI 2021. [paper]

42. Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network. Xiyue Zhang, Chao Huang, Yong Xu, Lianghao Xia, Peng Dai, Liefeng Bo, Junbo Zhang, Yu Zheng. AAAI 2021. [paper]

---2020---

1. An Attentional Recurrent Neural Network for Personalized Next Location Recommendation. Qing Guo, Zhu Sun, Jie Zhang, Yin-Leng Theng. AAAI 2020. [paper]

2. AirNet: A Calibration Model for Low-Cost Air Monitoring Sensors Using Dual Sequence Encoder Networks. Haomin Yu, Qingyong Li, Yangli-ao Geng, Yingjun Zhang, Zhi Wei. AAAI 2020. [paper]

3. A Simple, Fast, and Safe Mediator for Congestion Management. Kei Ikegami, Kyohei Okumura, Takumi Yoshikawa. AAAI 2020. [paper]

4. Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting. Qiquan Shi, Jiaming Yin, Jiajun Cai, Andrzej Cichocki, Tatsuya Yokota, Lei Chen, Mingxuan Yuan, Jia Zeng. AAAI 2020. [paper]

5. DATA-GRU: Dual-Attention Time-Aware Gated Recurrent Unit for Irregular Multivariate Time Series. Qingxiong Tan, Mang Ye, Baoyao Yang, Siqi Liu, Andy Jinhua Ma, Terry Cheuk-Fung Yip, Grace Lai-Hung Wong, PongChi Yuen. AAAI 2020. [paper]

6. DeepDualMapper: A Gated Fusion Network for Automatic Map Extraction Using Aerial Images and Trajectories. Hao Wu, Hanyuan Zhang, Xinyu Zhang, Weiwei Sun, Baihua Zheng, Yuning Jiang. AAAI 2020. [paper]

7. Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval. Dixian Zhu, Dongjin Song, Yuncong Chen, Cristian Lumezanu, Wei Cheng, Bo Zong, Jingchao Ni, Takehiko Mizoguchi, Tianbao Yang, Haifeng Chen. AAAI 2020. [paper]

8. Enhancing Personalized Trip Recommendation with Attractive Routes. Jiqing Gu, Chao Song, Wenjun Jiang, Xiaomin Wang, Ming Liu. AAAI 2020. [paper]

9. Event-Driven Continuous Time Bayesian Networks. Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian. AAAI 2020. [paper]

10. Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series. Zhi-Xuan Tan, Harold Soh, Desmond Ong. AAAI 2020. [paper]

11. GMAN: A Graph Multi-Attention Network for Traffic Prediction. Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, Jianzhong Qi. AAAI 2020. [paper]

12. Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values. Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang. AAAI 2020. [paper]

13. Learning Geo-Contextual Embeddings for Commuting Flow Prediction. Zhicheng Liu, Fabio Miranda, Weiting Xiong, Junyan Yang, Qiao Wang, Cláudio T. Silva. AAAI 2020. [paper]

14. Learning to Generate Maps from Trajectories. Sijie Ruan, Cheng Long, Jie Bao, Chunyang Li, Zisheng Yu, Ruiyuan Li, Yuxuan Liang, Tianfu He, Yu Zheng. AAAI 2020. [paper]

15. MetaLight: Value-Based Meta-Reinforcement Learning for Traffic Signal Control. Xinshi Zang, Huaxiu Yao, Guanjie Zheng, Nan Xu, Kai Xu, Zhenhui Li. AAAI 2020. [paper]

16. Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting. Weiqi Chen, Ling Chen, Yu Xie, Wei Cao, Yusong Gao, Xiaojie Feng. AAAI 2020. [paper]

17. OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting. Ding Wang, Boyang Liu, Pang-Ning Tan, Lifeng Luo. AAAI 2020. [paper]

18. Pay Your Trip for Traffic Congestion: Dynamic Pricing in Traffic-Aware Road Networks. Lisi Chen, Shuo Shang, Bin Yao, Jing Li. AAAI 2020. [paper]

19. Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development. Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Jinfeng Yi. AAAI 2020. [paper]

20. Real-Time Route Search by Locations. Lisi Chen, Shuo Shang, Tao Guo. AAAI 2020. [paper]

21. RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework. Zhengyang Zhou, Yang Wang, Xike Xie, Lianliang Chen, Hengchang Liu. AAAI 2020. [paper]

22. Spatio-Temporal Attention-Based Neural Network for Credit Card Fraud Detection. Dawei Cheng, Sheng Xiang, Chencheng Shang, Yiyi Zhang, Fangzhou Yang, Liqing Zhang. AAAI 2020. [paper]

23. Spatial Classification with Limited Observations Based on Physics-Aware Structural Constraint. Arpan Man Sainju, Wenchong He, Zhe Jiang, Da Yan. AAAI 2020. [paper]

24. Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting. Chao Song, Youfang Lin, Shengnan Guo, Huaiyu Wan. AAAI 2020. [paper]

25. Spatio-Temporal Graph Structure Learning for Traffic Forecasting. Qi Zhang, Jianlong Chang, Gaofeng Meng, Shiming Xiang, Chunhong Pan. AAAI 2020. [paper]

26. Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction. Weijia Zhang, Hao Liu, Yanchi Liu, Jingbo Zhou, Hui Xiong. AAAI 2020. [paper]

27. Self-Attention ConvLSTM for Spatiotemporal Prediction. Zhihui Lin, Maomao Li, Zhuobin Zheng, Yangyang Cheng, Chun Yuan. AAAI 2020. [paper]

28. Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series. Dongkuan Xu, Wei Cheng, Bo Zong, Dongjin Song, Jingchao Ni, Wenchao Yu, Yanchi Liu, Haifeng Chen, Xiang Zhang. AAAI 2020. [paper]

29. Toward A Thousand Lights: Decentralized Deep Reinforcement Learning for Large-Scale Traffic Signal Control. Chacha Chen, Hua Wei, Nan Xu, Guanjie Zheng, Ming Yang, Yuanhao Xiong, Kai Xu, Zhenhui Li. AAAI 2020. [paper]

30. Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets. Ziqiang Cheng, Yang Yang, Wei Wang, Wenjie Hu, Yueting Zhuang, Guojie Song. AAAI 2020. [paper]

31. Tensor Completion for Weakly-Dependent Data on Graph for Metro Passenger Flow Prediction. Ziyue Li, Nurettin Dorukhan Sergin, Hao Yan, Chen Zhang, Fugee Tsung. AAAI 2020. [paper]

32. TapNet: Multivariate Time Series Classification with Attentional Prototypical Network. Xuchao Zhang, Yifeng Gao, Jessica Lin, Chang-Tien Lu. AAAI 2020. [paper]

33. Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding. Zhecheng Wang, Haoyuan Li, Ram Rajagopal. AAAI 2020. [paper]

34. Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation. Ke Sun, Tieyun Qian, Tong Chen, Yile Liang, Quoc Viet Hung Nguyen, Hongzhi Yin. AAAI 2020. [paper]

---2019---

1. Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting. Shengnan Guo, Youfang Lin, Ning Feng, Chao Song, Huaiyu Wan. AAAI 2019. [paper]

2. A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems. Ling Pan, Qingpeng Cai, Zhixuan Fang, Pingzhong Tang, Longbo Huang. AAAI 2019. [paper]

3. A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data. Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla. AAAI 2019. [paper]

4. Congestion Graphs for Automated Time Predictions. Arik Senderovich, J. Christopher Beck, Avigdor Gal, Matthias Weidlich. [paper]

5. Deep Hierarchical Graph Convolution for Election Prediction from Geospatial Census Data. Mike Li, Elija Perrier, Chang Xu. AAAI 2019. [paper]

6. DeepETA: A Spatial-Temporal Sequential Neural Network Model for Estimating Time of Arrival in Package Delivery System. Fan Wu, Lixia Wu. AAAI 2019. [paper]

7. Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting. Zulong Diao, Xin Wang, Dafang Zhang, Yingru Liu, Kun Xie, Shaoyao He. AAAI 2019. [paper]

8. DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis. Ziqian Lin, Jie Feng, Ziyang Lu, Yong Li, Depeng Jin. AAAI 2019. [paper]

9. Efficient Region Embedding with Multi-View Spatial Networks: A Perspective of Locality-Constrained Spatial Autocorrelations. Yanjie Fu, Pengyang Wang, Jiadi Du, Le Wu, Xiaolin Li. AAAI 2019. [paper]

10. Estimating the Causal Effect from Partially Observed Time Series. Akane Iseki, Yusuke Mukuta, Yoshitaka Ushiku, Tatsuya Harada. AAAI 2019. [paper]

11. Gated Residual Recurrent Graph Neural Networks for Traffic Prediction. Cen Chen, Kenli Li, Sin G. Teo, Xiaofeng Zou, Kang Wang, Jie Wang, Zeng Zeng. AAAI 2019. [paper]

12. Incorporating Semantic Similarity with Geographic Correlation for Query-POI Relevance Learning. Ji Zhao, Dan Peng, Chuhan Wu, Huan Chen, Meiyu Yu, Wanji Zheng, Li Ma, Hua Chai, Jieping Ye, Xiaohu Qie. AAAI 2019. [paper]

13. Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. AAAI 2019. [paper]

14. Joint Representation Learning for Multi-Modal Transportation Recommendation. Hao Liu, Ting Li, Renjun Hu, Yanjie Fu, Jingjing Gu, Hui Xiong. AAAI 2019. [paper]

15. Learning Heterogeneous Spatial-Temporal Representation for Bike-Sharing Demand Prediction. Youru Li, Zhenfeng Zhu, Deqiang Kong, Meixiang Xu, Yao Zhao. AAAI 2019. [paper]

16. Modelling of Bi-Directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-In Identification. Dongbo Xi, Fuzhen Zhuang, Yanchi Liu, Jingjing Gu, Hui Xiong, Qing He. AAAI 2019. [paper]

17. Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data. Tomoharu Iwata, Hitoshi Shimizu. AAAI 2019. [paper]

18. Predicting Hurricane Trajectories Using a Recurrent Neural Network. Sheila Alemany, Jonathan Beltran, Adrián Pérez, Sam Ganzfried. AAAI 2019. [paper]

19. Region-Based Message Exploration over Spatio-Temporal Data Streams. Lisi Chen, Shuo Shang. AAAI 2019. [paper]

20. Spatiality Preservable Factored Poisson Regression for Large-Scale Fine-Grained GPS-Based Population Analysis. Masamichi Shimosaka, Yuta Hayakawa, Kota Tsubouchi. AAAI 2019. [paper]

21. Optimal Interdiction of Urban Criminals with the Aid of Real-Time Information. Youzhi Zhang, Qingyu Guo, Bo An, Long Tran-Thanh, Nicholas R. Jennings. AAAI 2019. [paper]

22. Preference-Aware Task Assignment in On-Demand Taxi Dispatching: An Online Stable Matching Approach. Boming Zhao, Pan Xu, Yexuan Shi, Yongxin Tong, Zimu Zhou, Yuxiang Zeng. AAAI 2019. [paper]

23. Preference-Aware Task Assignment in Spatial Crowdsourcing. Yan Zhao, Jinfu Xia, Guanfeng Liu, Han Su, Defu Lian, Shuo Shang, Kai Zheng. AAAI 2019. [paper]

24. Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data. Amin Vahedian, Xun Zhou, Ling Tong, W. Nick Street, Yanhua Li. AAAI 2019. [paper]

25. Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities. Yusuke Tanaka, Tomoharu Iwata, Toshiyuki Tanaka, Takeshi Kurashima, Maya Okawa, Hiroyuki Toda. AAAI 2019. [paper]

26. RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series. Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Huan Xu, Shenghuo Zhu. AAAI 2019. [paper]

27. Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction. Huaxiu Yao, Xianfeng Tang, Hua Wei, Guanjie Zheng, Zhenhui Li. AAAI 2019. [paper]

28. Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting. Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang, Jieping Ye, Yan Liu. AAAI 2019. [paper]

29. TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents. Yuexin Ma, Xinge Zhu, Sibo Zhang, Ruigang Yang, Wenping Wang, Dinesh Manocha. AAAI 2019. [paper]

30. Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation. Pengpeng Zhao, Haifeng Zhu, Yanchi Liu, Jiajie Xu, Zhixu Li, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou. AAAI 2019. [paper]