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Peng Chen, Yingying Zhang, Yunyao Cheng, Yang Shu, Yihang Wang, Qingsong Wen, Bin Yang, Chenjuan Guo: Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting. CoRR abs/2402.05956 (2024)
Xiangfei Qiu, Jilin Hu, Lekui Zhou, Xingjian Wu, Junyang Du, Buang Zhang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Zhenli Sheng, Bin Yang: TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods. CoRR abs/2403.20150 (2024)
David Campos, Bin Yang, Tung Kieu, Miao Zhang, Chenjuan Guo, Christian S. Jensen: QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models - Extended Version. CoRR abs/2404.13990 (2024)
Hao Miao, Yan Zhao, Chenjuan Guo, Bin Yang, Kai Zheng, Feiteng Huang, Jiandong Xie, Christian S. Jensen: A Unified Replay-based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data. CoRR abs/2404.14999 (2024)
Xinle Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang, Christian S. Jensen: AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting. Proc. ACM Manag. Data 1(1): 97:1-97:26 (2023)
David Campos, Miao Zhang, Bin Yang, Tung Kieu, Chenjuan Guo, Christian S. Jensen: LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation. Proc. ACM Manag. Data 1(2): 171:1-171:27 (2023)
Zhicheng Pan, Yihang Wang, Yingying Zhang, Sean Bin Yang, Yunyao Cheng, Peng Chen, Chenjuan Guo, Qingsong Wen, Xiduo Tian, Yunliang Dou, Zhiqiang Zhou, Chengcheng Yang, Aoying Zhou, Bin Yang: MagicScaler: Uncertainty-aware, Predictive Autoscaling. Proc. VLDB Endow. 16(12): 3808-3821 (2023)
Kai Zhao, Chenjuan Guo, Yunyao Cheng, Peng Han, Miao Zhang, Bin Yang: Multiple Time Series Forecasting with Dynamic Graph Modeling. Proc. VLDB Endow. 17(4): 753-765 (2023)
Yunyao Cheng, Peng Chen, Chenjuan Guo, Kai Zhao, Qingsong Wen, Bin Yang, Christian S. Jensen: Weakly Guided Adaptation for Robust Time Series Forecasting. Proc. VLDB Endow. 17(4): 766-779 (2023)
Haomin Yu, Jilin Hu, Xinyuan Zhou, Chenjuan Guo, Bin Yang, Qingyong Li: CGF: A Category Guidance Based PM$_{2.5}$ Sequence Forecasting Training Framework. IEEE Trans. Knowl. Data Eng. 35(10): 10125-10139 (2023)
Sean Bin Yang, Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen: LightPath: Lightweight and Scalable Path Representation Learning. KDD 2023: 2999-3010
David Campos, Miao Zhang, Bin Yang, Tung Kieu, Chenjuan Guo, Christian S. Jensen: LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation - Extended Version. CoRR abs/2302.12721 (2023)
Haomin Yu, Yanru Song, Jilin Hu, Chenjuan Guo, Bin Yang: A Crystal-Specific Pre-Training Framework for Crystal Material Property Prediction. CoRR abs/2306.05344 (2023)
Sean Bin Yang, Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen: LightPath: Lightweight and Scalable Path Representation Learning. CoRR abs/2307.10171 (2023)
Sean Bin Yang, Chenjuan Guo, Bin Yang: Context-Aware Path Ranking in Road Networks. IEEE Trans. Knowl. Data Eng. 34(7): 3153-3168 (2022)
Tung Kieu, Bin Yang, Chenjuan Guo, Razvan-Gabriel Cirstea, Yan Zhao, Yale Song, Christian S. Jensen: Anomaly Detection in Time Series with Robust Variational Quasi-Recurrent Autoencoders. ICDE 2022: 1342-1354
Sean Bin Yang, Chenjuan Guo, Jilin Hu, Bin Yang, Jian Tang, Christian S. Jensen: Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning. ICDE 2022: 2873-2885
Razvan-Gabriel Cirstea, Bin Yang, Chenjuan Guo, Tung Kieu, Shirui Pan: Towards Spatio- Temporal Aware Traffic Time Series Forecasting. ICDE 2022: 2900-2913
Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen, Yan Zhao, Feiteng Huang, Kai Zheng: Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection. ICDE 2022: 3038-3050
Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang, Tung Kieu, Xuanyi Dong, Shirui Pan: Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting. IJCAI 2022: 1994-2001
Shufang Xie, Rui Yan, Peng Han, Yingce Xia, Lijun Wu, Chenjuan Guo, Bin Yang, Tao Qin: RetroGraph: Retrosynthetic Planning with Graph Search. KDD 2022: 2120-2129
Miao Zhang, Li Wang, David Campos, Wei Huang, Chenjuan Guo, Bin Yang: Weighted Mutual Learning with Diversity-Driven Model Compression. NeurIPS 2022
Yan Zhao, Xuanhao Chen, Liwei Deng, Tung Kieu, Chenjuan Guo, Bin Yang, Kai Zheng, Christian S. Jensen: Outlier Detection for Streaming Task Assignment in Crowdsourcing. WWW 2022: 1933-1943
Razvan-Gabriel Cirstea, Bin Yang, Chenjuan Guo, Tung Kieu, Shirui Pan: Towards Spatio-Temporal Aware Traffic Time Series Forecasting-Full Version. CoRR abs/2203.15737 (2022)
Sean Bin Yang, Chenjuan Guo, Jilin Hu, Bin Yang, Jian Tang, Christian S. Jensen: Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning - Extended Version. CoRR abs/2203.16110 (2022)
Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen, Yan Zhao, Feiteng Huang, Kai Zheng: Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection - Extended Version. CoRR abs/2204.03341 (2022)
Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang, Tung Kieu, Xuanyi Dong, Shirui Pan: Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting-Full Version. CoRR abs/2204.13767 (2022)
Shufang Xie, Rui Yan, Peng Han, Yingce Xia, Lijun Wu, Chenjuan Guo, Bin Yang, Tao Qin: RetroGraph: Retrosynthetic Planning with Graph Search. CoRR abs/2206.11477 (2022)
Yan Zhao, Liwei Deng, Xuanhao Chen, Chenjuan Guo, Bin Yang, Tung Kieu, Feiteng Huang, Torben Bach Pedersen, Kai Zheng, Christian S. Jensen: A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis. CoRR abs/2209.04635 (2022)
Xinle Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang, Christian S. Jensen: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting. CoRR abs/2211.16126 (2022)
Xinle Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Shuai Zhao, Yi Zhang, Huai Wang, Bin Yang: AutoPINN: When AutoML Meets Physics-Informed Neural Networks. CoRR abs/2212.04058 (2022)
Yunyao Cheng, Chenjuan Guo, Kaixuan Chen, Kai Zhao, Bin Yang, Jiandong Xie, Christian S. Jensen, Feiteng Huang, Kai Zheng: A Pattern Discovery Approach to Multivariate Time Series Forecasting. CoRR abs/2212.10306 (2022)
David Campos, Tung Kieu, Chenjuan Guo, Feiteng Huang, Kai Zheng, Bin Yang, Christian S. Jensen: Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles. Proc. VLDB Endow. 15(3): 611-623 (2021)
Xinle Wu, Dalin Zhang, Chenjuan Guo, Chaoyang He, Bin Yang, Christian S. Jensen: AutoCTS: Automated Correlated Time Series Forecasting. Proc. VLDB Endow. 15(4): 971-983 (2021)
Razvan-Gabriel Cirstea, Tung Kieu, Chenjuan Guo, Bin Yang, Sinno Jialin Pan: EnhanceNet: Plugin Neural Networks for Enhancing Correlated Time Series Forecasting. ICDE 2021: 1739-1750
Sean Bin Yang, Chenjuan Guo, Jilin Hu, Jian Tang, Bin Yang: Unsupervised Path Representation Learning with Curriculum Negative Sampling. IJCAI 2021: 3286-3292
Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang: Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting - Full version. CoRR abs/2103.10760 (2021)
Sean Bin Yang, Chenjuan Guo, Jilin Hu, Jian Tang, Bin Yang: Unsupervised Path Representation Learning with Curriculum Negative Sampling. CoRR abs/2106.09373 (2021)
David Campos, Tung Kieu, Chenjuan Guo, Feiteng Huang, Kai Zheng, Bin Yang, Christian S. Jensen: Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles - Extended Version. CoRR abs/2111.11108 (2021)
Xinle Wu, Dalin Zhang, Chenjuan Guo, Chaoyang He, Bin Yang, Christian S. Jensen: AutoCTS: Automated Correlated Time Series Forecasting - Extended Version. CoRR abs/2112.11174 (2021)
Chenjuan Guo, Bin Yang, Jilin Hu, Christian S. Jensen, Lu Chen: Context-aware, preference-based vehicle routing. VLDB J. 29(5): 1149-1170 (2020)
Jilin Hu, Bin Yang, Chenjuan Guo, Christian S. Jensen, Hui Xiong: Stochastic Origin-Destination Matrix Forecasting Using Dual-Stage Graph Convolutional, Recurrent Neural Networks. ICDE 2020: 1417-1428
Nicolaj Casanova Abildgaard, Casper Weiss Bang, Jonas Hansen, Tobias Lambek Jacobsen, Thomas H?jriis Knudsen, Nichlas ?rts Lisby, Chenjuan Guo, Bin Yang: A Correlated Time Series Forecast System. MDM 2020: 242-243
Lu Chen, Yunjun Gao, Ziquan Fang, Xiaoye Miao, Christian S. Jensen, Chenjuan Guo: Real-time Distributed Co-Movement Pattern Detection on Streaming Trajectories. Proc. VLDB Endow. 12(10): 1208-1220 (2019)
Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen: Stochastic Weight Completion for Road Networks Using Graph Convolutional Networks. ICDE 2019: 1274-1285
Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen: Outlier Detection for Time Series with Recurrent Autoencoder Ensembles. IJCAI 2019: 2725-2732
Bin Yang, Jian Dai, Chenjuan Guo, Christian S. Jensen, Jilin Hu: PACE: a PAth-CEntric paradigm for stochastic path finding. VLDB J. 27(2): 153-178 (2018)
Jilin Hu, Bin Yang, Chenjuan Guo, Christian S. Jensen: Risk-aware path selection with time-varying, uncertain travel costs: a time series approach. VLDB J. 27(2): 179-200 (2018)
Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen: Distinguishing Trajectories from Different Drivers using Incompletely Labeled Trajectories. CIKM 2018: 863-872
Razvan-Gabriel Cirstea, Darius-Valer Micu, Gabriel-Marcel Muresan, Chenjuan Guo, Bin Yang: Correlated Time Series Forecasting using Multi-Task Deep Neural Networks. CIKM 2018: 1527-1530
Chenjuan Guo, Bin Yang, Jilin Hu, Christian S. Jensen: Learning to Route with Sparse Trajectory Sets. ICDE 2018: 1073-1084
Chenjuan Guo, Bin Yang, Jilin Hu, Christian S. Jensen: Learning to Route with Sparse Trajectory Sets - Extended Version. CoRR abs/1802.07980 (2018)
Razvan-Gabriel Cirstea, Darius-Valer Micu, Gabriel-Marcel Muresan, Chenjuan Guo, Bin Yang: Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results. CoRR abs/1808.09794 (2018)
Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen, Lu Chen: Recurrent Multi-Graph Neural Networks for Travel Cost Prediction. CoRR abs/1811.05157 (2018)
Jian Dai, Bin Yang, Chenjuan Guo, Christian S. Jensen, Jilin Hu: Path Cost Distribution Estimation Using Trajectory Data. Proc. VLDB Endow. 10(3): 85-96 (2016)
Hua Lu, Chenjuan Guo, Bin Yang, Christian S. Jensen: Finding Frequently Visited Indoor POIs Using Symbolic Indoor Tracking Data. EDBT 2016: 449-460
Chenjuan Guo, Bin Yang, Ove Andersen, Christian S. Jensen, Kristian Torp: EcoMark 2.0: empowering eco-routing with vehicular environmental models and actual vehicle fuel consumption data. GeoInformatica 19(3): 567-599 (2015)
Bin Yang, Chenjuan Guo, Yu Ma, Christian S. Jensen: Toward personalized, context-aware routing. VLDB J. 24(2): 297-318 (2015)
Jian Dai, Bin Yang, Chenjuan Guo, Zhiming Ding: Personalized route recommendation using big trajectory data. ICDE 2015: 543-554
Chenjuan Guo, Bin Yang, Ove Andersen, Christian S. Jensen, Kristian Torp: EcoSky: Reducing vehicular environmental impact through eco-routing. ICDE 2015: 1412-1415
Jian Dai, Bin Yang, Chenjuan Guo, Christian S. Jensen: Efficient and Accurate Path Cost Estimation Using Trajectory Data. CoRR abs/1510.02886 (2015)
Chenjuan Guo, Christian S. Jensen, Bin Yang: Towards Total Traffic Awareness. SIGMOD Rec. 43(3): 18-23 (2014)
Bin Yang, Chenjuan Guo, Christian S. Jensen, Manohar Kaul, Shuo Shang: Stochastic skyline route planning under time-varying uncertainty. ICDE 2014: 136-147
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