Deep Fourier Kernel for Self-Attentive Point Processes [article]

Shixiang Zhu, Minghe Zhang, Ruyi Ding, Yao Xie
2021 arXiv   pre-print
We present a novel attention-based model for discrete event data to capture complex non-linear temporal dependence structures. We borrow the idea from the attention mechanism and incorporate it into the point processes' conditional intensity function. We further introduce a novel score function using Fourier kernel embedding, whose spectrum is represented using neural networks, which drastically differs from the traditional dot-product kernel and can capture a more complex similarity structure.
more » ... We establish our approach's theoretical properties and demonstrate our approach's competitive performance compared to the state-of-the-art for synthetic and real data.
arXiv:2002.07281v5 fatcat:ubmconvmdvgt3knvc3ehbchm7i