3 papers
eess.SP2026
A Mixture-of-Experts Framework for Multi-Stream Quickest Change Detection
Wuxia Chen, Arman Adibi, Taposh Banerjee +1
A Mixture-of-Experts (MoE) framework is proposed for quickest change detection (QCD) where there are multiple experts, and each expert produces a sequence of statistics for change…
eess.SP2025
Score-Based Quickest Change Detection and Fault Identification for Multi-Stream Signals
Wuxia Chen, Sean Moushegian, Vahid Tarokh +1
This paper introduces an approach to multi-stream quickest change detection and fault isolation for unnormalized and score-based statistical models. Traditional optimal algorithms…
cs.LG2025
Conditional Score Learning for Quickest Change Detection in Markov Transition Kernels
Wuxia Chen, Taposh Banerjee, Vahid Tarokh
We address the problem of quickest change detection in Markov processes with unknown transition kernels. The key idea is to learn the conditional score $\nabla_{\mathbf{y}} \log p(…