By Dr Hao Xue

Book Chapters

Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, 'Continually Learning Out-of-Distribution Spatiotemporal Data for Robust Energy Forecasting', in , pp. 3 - 19, http://dx.doi.org/10.1007/978-3-031-43430-3_1

Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, 'Correction to: Continually Learning Out-of-Distribution Spatiotemporal Data for Robust Energy Forecasting', in Lecture Notes in Computer Science, Springer Nature Switzerland, pp. C1 - C2, http://dx.doi.org/10.1007/978-3-031-43430-3_34

Xue H; Huynh DQ; Reynolds M, 2020, 'Take a NAP: Non-Autoregressive Prediction for Pedestrian Trajectories', in , pp. 544 - 556, http://dx.doi.org/10.1007/978-3-030-63830-6_46

Xue H; Huynh DQ; Reynolds M, 2019, 'Pedestrian Trajectory Prediction Using a Social Pyramid', in , pp. 439 - 453, http://dx.doi.org/10.1007/978-3-030-29911-8_34

Sun P; Tian R; Xue H; Wan K, 2016, 'Development and analysis of police digital trunking channel technology of PDT', in , pp. 189 - 199, http://dx.doi.org/10.1007/978-81-322-2580-5_19

Journal articles

Züfle A; Salim F; Anderson T; Scotch M; Xiong L; Sokol K; Xue H; Kong R; Heslop D; Paik H-Y; MacIntyre CR, 2024, 'Leveraging Simulation Data to Understand Bias in Predictive Models of Infectious Disease Spread', ACM Transactions on Spatial Algorithms and Systems, 10, pp. 1 - 22, http://dx.doi.org/10.1145/3660631

Prabowo A; Xue H; Shao W; Koniusz P; Salim FD, 2024, 'Traffic forecasting on new roads using spatial contrastive pre-training (SCPT)', Data Mining and Knowledge Discovery, 38, pp. 913 - 937, http://dx.doi.org/10.1007/s10618-023-00982-0

Khaokaew Y; Xue H; Salim FD, 2024, 'MAPLE: Mobile App Prediction Leveraging Large Language Model Embeddings', Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 8, http://dx.doi.org/10.1145/3643514

Wang Z; Jiang R; Xue H; Salim FD; Song X; Shibasaki R; Hu W; Wang S, 2024, 'Learning spatio-temporal dynamics on mobility networks for adaptation to open-world events', Artificial Intelligence, pp. 104120 - 104120, http://dx.doi.org/10.1016/j.artint.2024.104120

Xue H; Salim FD, 2023, 'PromptCast: A New Prompt-Based Learning Paradigm for Time Series Forecasting', IEEE Transactions on Knowledge and Data Engineering, http://dx.doi.org/10.1109/TKDE.2023.3342137

Deldari S; Xue H; Saeed A; Smith DV; Salim FD, 2022, 'COCOA: Cross Modality Contrastive Learning for Sensor Data', Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 6, http://dx.doi.org/10.1145/3550316

Wang Z; Jiang R; Xue H; Salim FD; Song X; Shibasaki R, 2022, 'Event-Aware Multimodal Mobility Nowcasting', Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, 36, pp. 4228 - 4236

Gao N; Xue H; Shao W; Zhao S; Qin KK; Prabowo A; Rahaman MS; Salim FD, 2022, 'Generative Adversarial Networks for Spatio-temporal Data: A Survey', ACM Transactions on Intelligent Systems and Technology, 13, http://dx.doi.org/10.1145/3474838

Dong B; Liu Y; Fontenot H; Ouf M; Osman M; Chong A; Qin S; Salim F; Xue H; Yan D; Jin Y; Han M; Zhang X; Azar E; Carlucci S, 2021, 'Occupant behavior modeling methods for resilient building design, operation and policy at urban scale: A review', Applied Energy, 293, http://dx.doi.org/10.1016/j.apenergy.2021.116856

Xu L; Xue H; Bennamoun M; Boussaid F; Sohel F, 2021, 'Atrous convolutional feature network for weakly supervised semantic segmentation', Neurocomputing, 421, pp. 115 - 126, http://dx.doi.org/10.1016/j.neucom.2020.09.045

Xue H; Huynh DQ; Reynolds M, 2021, 'PoPPL: Pedestrian Trajectory Prediction by LSTM with Automatic Route Class Clustering', IEEE Transactions on Neural Networks and Learning Systems, 32, pp. 77 - 90, http://dx.doi.org/10.1109/TNNLS.2020.2975837

Yang X; Yu X; Xie L; Xue H; Zhou M; Jiang Q, 2021, 'Sleep Apnea Monitoring System Based on Commodity WiFi Devices', Computers, Materials and Continua, 69, pp. 2793 - 2806, http://dx.doi.org/10.32604/cmc.2021.016298

Xue H; Huynh DQ; Reynolds M, 2020, 'A Location-Velocity-Temporal Attention LSTM Model for Pedestrian Trajectory Prediction', IEEE Access, 8, pp. 44576 - 44589, http://dx.doi.org/10.1109/ACCESS.2020.2977747

Feng G; Ma L; Tan X; Xue H; Guan K, 2016, 'Visual Location Recognition Based on Coarse-to-Fine Image Retrieval and Epipolar Geometry Constraint for Urban Environment', International Journal of Signal Processing, Image Processing and Pattern Recognition, 9, pp. 25 - 36, http://dx.doi.org/10.14257/ijsip.2016.9.11.03

Conference Papers

Li P; de Rijke M; Xue H; Ao S; Song Y; Salim FD, 2024, 'Large Language Models for Next Point-of-Interest Recommendation', in Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM, presented at SIGIR 2024: The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, http://dx.doi.org/10.1145/3626772.3657840

Yang R; Salim FD; Xue H, 2024, 'SSTKG: Simple Spatio-Temporal Knowledge Graph for Intepretable and Versatile Dynamic Information Embedding', in WWW 2024 - Proceedings of the ACM Web Conference, pp. 551 - 559, http://dx.doi.org/10.1145/3589334.3645441

Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, 'Navigating Out-of-Distribution Electricity Load Forecasting during COVID-19: Benchmarking energy load forecasting models without and with continual learning', in BuildSys 2023 - Proceedings of the10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, pp. 41 - 50, http://dx.doi.org/10.1145/3600100.3623726

Xue H; Salim FD, 2023, 'Utilizing Language Models for Energy Load Forecasting', in BuildSys 2023 - Proceedings of the10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, pp. 224 - 227, http://dx.doi.org/10.1145/3600100.3623730

Xue H; Salim FD, 2023, 'Artificial General Intelligence for Human Mobility (Vision Paper)', in GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, http://dx.doi.org/10.1145/3589132.3625652

Khaokaew Y; Salim FD; Xue H, 2023, 'Understanding Mobile Information Needs and Behaviours', in UbiComp/ISWC 2023 Adjunct - Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2023 ACM International Symposium on Wearable Computing, pp. 210 - 214, http://dx.doi.org/10.1145/3594739.3610760

Prabowo A; Shao W; Xue H; Koniusz P; Salim FD, 2023, 'Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting', in ACM International Conference Proceeding Series, pp. 93 - 104, http://dx.doi.org/10.1145/3576842.3582362

Liu J; Deldari S; Xue H; Nguyen V; Salim FD, 2023, 'Self-supervised Activity Representation Learning with Incremental Data: An Empirical Study', in Proceedings - IEEE International Conference on Mobile Data Management, pp. 39 - 44, http://dx.doi.org/10.1109/MDM58254.2023.00019

Xue H; Voutharoja BP; Salim FD, 2022, 'Leveraging language foundation models for human mobility forecasting', in GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, http://dx.doi.org/10.1145/3557915.3561026

Xue H; Salim FD; Ren Y; Clarke CLA, 2022, 'Translating human mobility forecasting through natural language generation', in WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining, pp. 1224 - 1233, http://dx.doi.org/10.1145/3488560.3498387

Xue H; Salim FD, 2021, 'Exploring Self-Supervised Representation Ensembles for COVID-19 Cough Classification', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1944 - 1952, http://dx.doi.org/10.1145/3447548.3467263

Deldari S; Smith DV; Xue H; Salim FD, 2021, 'Time series change point detection with self-supervised contrastive predictive coding', in The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021, pp. 3124 - 3135, http://dx.doi.org/10.1145/3442381.3449903

Xue H; Salim FD; Ren Y; Oliver N, 2021, 'MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction', in Advances in Neural Information Processing Systems, pp. 30380 - 30391

Abushaqra FM; Xue H; Ren Y; Salim FD, 2021, 'PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series', in Proceedings - IEEE International Conference on Data Mining, ICDM, pp. 976 - 981, http://dx.doi.org/10.1109/ICDM51629.2021.00109

Xue H; Salim FD, 2021, 'TERMCast: Temporal Relation Modeling for Effective Urban Flow Forecasting', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 741 - 753, http://dx.doi.org/10.1007/978-3-030-75762-5_58

Xue H; Huynh DQ; Reynolds M, 2019, 'Pedestrian tracking and stereo matching of tracklets for autonomous vehicles', in IEEE Vehicular Technology Conference, http://dx.doi.org/10.1109/VTCSpring.2019.8746329

Xue H; Huynh DQ; Reynolds M, 2019, 'Location-velocity attention for pedestrian trajectory prediction', in Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019, pp. 2038 - 2047, http://dx.doi.org/10.1109/WACV.2019.00221

Xue H; Huynh DQ; Reynolds M, 2018, 'SS-LSTM: A Hierarchical LSTM Model for Pedestrian Trajectory Prediction', in Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018, pp. 1186 - 1194, http://dx.doi.org/10.1109/WACV.2018.00135

Xue H; Huynh DQ; Reynolds M, 2017, 'Bi-prediction: Pedestrian trajectory prediction based on bidirectional LSTM classification', in DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications, pp. 1 - 8, http://dx.doi.org/10.1109/DICTA.2017.8227412

Ma L; Xue H; Jia T; Tan X, 2017, 'A Fast C-GIST Based Image Retrieval Method for Vision-Based Indoor Localization', in IEEE Vehicular Technology Conference, http://dx.doi.org/10.1109/VTCSpring.2017.8108338

Xue H; Ma L; Tan X, 2016, 'A fast visual map building method using video stream for visual-based indoor localization', in 2016 International Wireless Communications and Mobile Computing Conference, IWCMC 2016, pp. 650 - 654, http://dx.doi.org/10.1109/IWCMC.2016.7577133

Preprints

Li P; Rijke MD; Xue H; Ao S; Song Y; Salim FD, 2024, Large Language Models for Next Point-of-Interest Recommendation, , http://dx.doi.org/10.1145/3626772.3657840

Xue H; Tang T; Payani A; Salim FD, 2024, Prompt Mining for Language-based Human Mobility Forecasting, , http://arxiv.org/abs/2403.03544v1

Yang R; Salim FD; Xue H, 2024, SSTKG: Simple Spatio-Temporal Knowledge Graph for Intepretable and Versatile Dynamic Information Embedding, , http://arxiv.org/abs/2402.12132v1

Xue H; Salim FD, 2023, Utilizing Language Models for Energy Load Forecasting, , http://arxiv.org/abs/2310.17788v1

Xue H; Salim FD, 2023, Human Mobility Question Answering (Vision Paper), , http://arxiv.org/abs/2310.04443v2

Khaokaew Y; Xue H; Salim FD, 2023, MAPLE: Mobile App Prediction Leveraging Large Language Model Embeddings, , http://dx.doi.org/10.48550/arxiv.2309.08648

Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, Navigating Out-of-Distribution Electricity Load Forecasting during COVID-19: Benchmarking energy load forecasting models without and with continual learning, , http://dx.doi.org/10.1145/3600100.3623726

Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, Continually learning out-of-distribution spatiotemporal data for robust energy forecasting, , http://dx.doi.org/10.1007/978-3-031-43430-3_1

Prabowo A; Xue H; Shao W; Koniusz P; Salim FD, 2023, Message Passing Neural Networks for Traffic Forecasting, , http://arxiv.org/abs/2305.05740v1

Prabowo A; Xue H; Shao W; Koniusz P; Salim FD, 2023, Traffic Forecasting on New Roads Using Spatial Contrastive Pre-Training (SCPT), , http://dx.doi.org/10.1007/s10618-023-00982-0

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