ORCID as entered in ROS
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Select Publications
2023, Self-supervised Activity Representation Learning with Incremental Data: An Empirical Study, , http://dx.doi.org/10.48550/arxiv.2305.00619
,2023, Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting, , http://dx.doi.org/10.1145/3576842.3582362
,2022, SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time Series, , http://arxiv.org/abs/2212.03560v2
,2022, PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecasting, , http://arxiv.org/abs/2210.08964v5
,2022, Leveraging Language Foundation Models for Human Mobility Forecasting, , http://arxiv.org/abs/2209.05479v2
,2022, COCOA: Cross Modality Contrastive Learning for Sensor Data, , http://dx.doi.org/10.1145/3550316
,2022, Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data, , http://arxiv.org/abs/2206.02353v2
,2021, Event-Aware Multimodal Mobility Nowcasting, , http://arxiv.org/abs/2112.08443v1
,2021, Translating Human Mobility Forecasting through Natural Language Generation, , http://arxiv.org/abs/2112.11481v1
,2021, PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series, , http://arxiv.org/abs/2110.00071v2
,2021, MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction, , http://arxiv.org/abs/2110.01401v1
,2021, Exploring Self-Supervised Representation Ensembles for COVID-19 Cough Classification, , http://dx.doi.org/10.1145/3447548.3467263
,2020, Time Series Change Point Detection with Self-Supervised Contrastive Predictive Coding, , http://dx.doi.org/10.1145/3442381.3449903
,2020, TERMCast: Temporal Relation Modeling for Effective Urban Flow Forecasting, , http://dx.doi.org/10.1007/978-3-030-75762-5_58
,2020, Scene Gated Social Graph: Pedestrian Trajectory Prediction Based on Dynamic Social Graphs and Scene Constraints, , http://arxiv.org/abs/2010.05507v1
,2020, Generative Adversarial Networks for Spatio-temporal Data: A Survey, , http://dx.doi.org/10.1145/3474838
,2020, Take a NAP: Non-Autoregressive Prediction for Pedestrian Trajectories, , http://arxiv.org/abs/2004.09760v1
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