Benefits from Superposed Hawkes Processes

Assessing the contagiousness of mass shootings with nonparametric Hawkes processes

Gun violence and mass shootings are high-profile epidemiological issues facing the United States with questions regarding their contagiousness gaining prevalence in news media. Through the use of nonparametric Hawkes processes, we examine the evidence for the existence of contagiousness within a catalog of mass shootings and highlight the broader benefits of using such nonparametric point process models in modeling the occurrence of such events.

Self-Attentive Hawkes Processes

Asynchronous events on the continuous time domain, e.g., social media actions and stock transactions, occur frequently in the world. The ability to recognize occurrence patterns of event sequences is crucial to predict which typeof events will happen next and when. A de facto standard mathematical framework to do this is the Hawkes process. In order to enhance expressivity of multivariate Hawkes processes, conventional statistical methods and deep recurrent networks have been employed to modify its intensity function. The former is highly interpretable and requires small size of training data …

从Hawkes过程到注意力：事件序列的时间调节机制

From Hawkes Processes to Attention: Time-Modulated Mechanisms for Event Sequences

本文提出Hawkes注意力机制，通过可学习的类型特定神经核调节查询、键和值投影，统一事件时间和内容交互，提升事件序列建模性能。

Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model

Health risks from cigarette smoking -- the leading cause of preventable death in the United States -- can be substantially reduced by quitting. Although most smokers are motivated to quit, the majority of quit attempts fail. A number of studies have explored the role of self-reported symptoms, physiologic measurements, and environmental context on smoking risk, but less work has focused on the temporal dynamics of smoking events, including daily patterns and related nicotine effects. In this work, we examine these dynamics and improve risk prediction by modeling smoking as a self-triggering pr…

具有抑制效应的多变量指数Hawkes过程的推断及其在神经元活动中的应用

Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity

本文研究同时具有激发和抑制效应的多维指数Hawkes过程的参数推断，提出频率学派框架下首个基于最大似然的精确推断方法，证明了模型可识别性，并在合成与神经元数据上验证了其优越性。

具有自适应时间步长的神经微分循环神经网络

Neural Differential Recurrent Neural Network with Adaptive Time Steps

针对含尖峰的非平稳时间序列，提出RNN-ODE-Adap，用神经ODE演化隐状态并按变化陡度自适应选步，兼具一致性理论保证与更高精度、更低成本。