36 citations · 126 across the 14 of their papers we have counts for
6 papers · 1 filter
Intensity-free Integral-based Learning of Marked Temporal Point Processes
Sishun Liu, Ke Deng, Xiuzhen Zhang +1
In the marked temporal point processes (MTPP), a core problem is to parameterize the conditional joint PDF (probability distribution function) for inter-event time a…
Multiple-level Point Embedding for Solving Human Trajectory Imputation with Prediction
Kyle K. Qin, Yongli Ren, Wei Shao +3
Sparsity is a common issue in many trajectory datasets, including human mobility data. This issue frequently brings more difficulty to relevant learning tasks, such as trajectory i…
SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time Series
Futoon M. Abushaqra, Hao Xue, Yongli Ren +1
Ordinary Differential Equations (ODE) based models have become popular as foundation models for solving many time series problems. Combining neural ODEs with traditional RNN models…
PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series
Futoon M. Abushaqra, Hao Xue, Yongli Ren +1
Heterogeneity and irregularity of multi-source data sets present a significant challenge to time-series analysis. In the literature, the fusion of multi-source time-series has been…
MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction
Hao Xue, Flora D. Salim, Yongli Ren +1
Human mobility prediction is a core functionality in many location-based services and applications. However, due to the sparsity of mobility data, it is not an easy task to predict…
Relation Embedding for Personalised POI Recommendation
Xianjing Wang, Flora D. Salim, Yongli Ren +1
Point-of-Interest (POI) recommendation is one of the most important location-based services helping people discover interesting venues or services. However, the extreme user-POI ma…