8 papers
Efficient Temporal Point Processes via Monotone Alternating Splines
Cheng Wan, Quyu Kong, Feng Zhou
Temporal point processes (TPPs) have widespread applications across various domains. Compared to modeling the conditional intensity of a TPP, modeling its cumulative conditional in…
Advances in Temporal Point Processes: Bayesian, Neural, and LLM Approaches
Feng Zhou, Quyu Kong, Jie Qiao +3
Temporal point processes (TPPs) are stochastic process models used to characterize event sequences occurring in continuous time. Traditional statistical TPPs have a long-standing h…
Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling
Yixuan Zhang, Jinhao Sheng, Wenxin Zhang +2
Although artificial neural networks are often described as brain-inspired, their representations typically rely on continuous activations, such as the continuous latent variables i…
Byte-token Enhanced Language Models for Temporal Point Processes Analysis
Quyu Kong, Yixuan Zhang, Yang Liu +3
Temporal Point Processes (TPPs) have been widely used for modeling event sequences on the Web, such as user reviews, social media posts, and online transactions. However, tradition…
Long-range Modeling and Processing of Multimodal Event Sequences
Jichu Li, Yilun Zhong, Zhiting Li +2
Temporal point processes (TPPs) have emerged as powerful tools for modeling asynchronous event sequences. While recent advances have extended TPPs to handle textual information, ex…
Fair Bayesian Data Selection via Generalized Discrepancy Measures
Yixuan Zhang, Jiabin Luo, Zhenggang Wang +2
Fairness concerns are increasingly critical as machine learning models are deployed in high-stakes applications. While existing fairness-aware methods typically intervene at the mo…