ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.03572
  4. Cited By
Detecting Abrupt Changes in High-Dimensional Self-Exciting Poisson
  Processes

Detecting Abrupt Changes in High-Dimensional Self-Exciting Poisson Processes

5 June 2020
Daren Wang
Yi Yu
Rebecca Willett
ArXivPDFHTML

Papers citing "Detecting Abrupt Changes in High-Dimensional Self-Exciting Poisson Processes"

4 / 4 papers shown
Title
Online Score Statistics for Detecting Clustered Change in Network Point
  Processes
Online Score Statistics for Detecting Clustered Change in Network Point Processes
Rui Zhang
Haoyun Wang
Yao Xie
39
1
0
16 Jun 2022
Sequential change-point detection for mutually exciting point processes
  over networks
Sequential change-point detection for mutually exciting point processes over networks
Haoyun Wang
Liyan Xie
Yao Xie
Alex Cuozzo
Simon Mak
11
12
0
10 Feb 2021
Bayesian latent structure discovery from multi-neuron recordings
Bayesian latent structure discovery from multi-neuron recordings
Scott W. Linderman
Ryan P. Adams
Jonathan W. Pillow
15
54
0
26 Oct 2016
Break detection in the covariance structure of multivariate time series
  models
Break detection in the covariance structure of multivariate time series models
Alexander Aue
Siegfried Hormann
Lajos Horváth
M. Reimherr
164
362
0
19 Nov 2009
1