2 citations · 5 across the 11 of their papers we have counts for
11 papers
Structured Neural Marked Point Processes for Interpretable Event Interaction Modeling
Zhitong Xu, Qiwei Yuan, Yinghao Chen +2
Multi-class event streams arise in numerous real-world applications, where uncovering structured, interpretable inter-event relationships, together with accurate prediction, remain…
Arbitrarily Conditioned Hierarchical Flows for Spatiotemporal Events
Keyan Chen, Qiwei Yuan, Zhitong Xu +2
Events in spatiotemporal systems are ubiquitous, yet modeling their complex distributions remains challenging. Existing point process models often rely on strong structural assumpt…
Focus and Dilution: The Multi-stage Learning Process of Attention
Zheng-An Chen, Pengxiao Lin, Zhi-Qin John Xu +1
Transformer-based models have achieved remarkable success across a wide range of domains, yet our understanding of their training dynamics remains limited. In this work, we identif…
Kronecker-Structured Nonparametric Spatiotemporal Point Processes
Zhitong Xu, Qiwei Yuan, Yinghao Chen +3
Events in spatiotemporal domains arise in numerous real-world applications, where uncovering event relationships and enabling accurate prediction are central challenges. Classical…
Deep Gaussian Processes for Functional Maps
Matthew Lowery, Zhitong Xu, Da Long +5
Learning mappings between functional spaces, also known as function-on-function regression, is a fundamental problem in functional data analysis with broad applications, including…
Tensor Gaussian Processes: Efficient Solvers for Nonlinear PDEs
Qiwei Yuan, Zhitong Xu, Yinghao Chen +3
Machine learning solvers for partial differential equations (PDEs) have attracted growing interest. However, most existing approaches, such as neural network solvers, rely on stoch…