Cover Image

Neural network-based CUSUM for online change-point detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gong, Tingnan, Lee, Junghwan, Cheng, Xiuyuan, Xie, Yao
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Computing high-dimensional optimal transport by flow neural networks
by: Xu, Chen, et al.
Published: (2023)

Higher-criticism for sparse multi-stream change-point detection
by: Gong, Tingnan, et al.
Published: (2024)

Flow-based Distributionally Robust Optimization
by: Xu, Chen, et al.
Published: (2023)

Online Kernel CUSUM for Change-Point Detection
by: Wei, Song, et al.
Published: (2022)

Point processes with event time uncertainty
by: Cheng, Xiuyuan, et al.
Published: (2024)

Score-based change point detection via tracking the best of infinitely many experts
by: Markovich, Anna, et al.
Published: (2024)

High-dimensional Mean-Field Games by Particle-based Flow Matching
by: Yu, Jiajia, et al.
Published: (2025)

Distribution-Free Online Change Detection for Low-Rank Images
by: Gong, Tingnan, et al.
Published: (2024)

Consistent and powerful CUSUM change-point test for panel data with changes in variance
by: Yang, Wenzhi, et al.
Published: (2026)

WISER: Segmenting watermarked region - an epidemic change-point perspective
by: Bonnerjee, Soham, et al.
Published: (2025)

Distribution-free changepoint localization after sequential change detection
by: Saha, Aytijhya, et al.
Published: (2026)

Neural networks for geospatial data
by: Zhan, Wentao, et al.
Published: (2023)

DoFlow: Flow-based Generative Models for Interventional and Counterfactual Forecasting on Time Series
by: Wu, Dongze, et al.
Published: (2025)

Setting the duration of online A/B experiments
by: Li, Harrison H., et al.
Published: (2024)

Adversarial Transform Particle Filters
by: Gong, Chengxin, et al.
Published: (2025)

Normalizing flow neural networks by JKO scheme
by: Xu, Chen, et al.
Published: (2022)

Training of Spiking Neural Networks with Expectation-Propagation
by: Yao, Dan, et al.
Published: (2025)

Flow-based generative models as iterative algorithms in probability space
by: Xie, Yao, et al.
Published: (2025)

Practical considerations when designing an online learning algorithm for an app-based mHealth intervention
by: Gonzalez, Rachel T, et al.
Published: (2025)

Nonparametric estimation of time-varying network connections by multi-stage smoothing
by: Lee, Jeonghwan, et al.
Published: (2026)

An alternative approach to train neural networks using monotone variational inequality
by: Xu, Chen, et al.
Published: (2022)

Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments
by: Xie, Feng, et al.
Published: (2024)

Cross-validation for change-point regression: pitfalls and solutions
by: Pein, Florian, et al.
Published: (2021)

Importance sampling for online variational learning
by: Chagneux, Mathis, et al.
Published: (2024)

Deep spatio-temporal point processes: Advances and new directions
by: Cheng, Xiuyuan, et al.
Published: (2025)

SMART Fine-tuning Factor Augmented Neural Lasso
by: Chai, Jinhang, et al.
Published: (2026)

An interpretable neural network-based non-proportional odds model for ordinal regression
by: Okuno, Akifumi, et al.
Published: (2023)

Deep graph kernel point processes
by: Dong, Zheng, et al.
Published: (2023)

Nonparametric efficient inference for network quantile causal effects under partial interference
by: Cheng, Chao, et al.
Published: (2026)

Flow-based Conformal Prediction for Multi-dimensional Time Series
by: Lee, Junghwan, et al.
Published: (2025)

A spectral approach for online covariance change point detection
by: Bao, Zhigang, et al.
Published: (2026)

Deep-testing: the case of dependence detection
by: Geenens, Gery, et al.
Published: (2026)

Multilayer random dot product graphs: Estimation and online change point detection
by: Wang, Fan, et al.
Published: (2023)

BLAST: Bayesian online change-point detection with structured image data
by: Zheng, Xiaojun, et al.
Published: (2025)

Benchmark of Likelihood-Free Inference Methods based on Neural and Optimal Transport Approaches
by: Aka, Samira, et al.
Published: (2026)

Optimal Kernel Choice for Score Function-based Causal Discovery
by: Wang, Wenjie, et al.
Published: (2024)

A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity
by: Lin, Jiahe, et al.
Published: (2024)

Improved prediction of future user activity in online A/B testing
by: Masoero, Lorenzo, et al.
Published: (2024)

Online LLM watermark detection via e-processes
by: Su, Weijie, et al.
Published: (2026)

Nonparametric estimation of conditional probability distributions using a generative approach based on conditional push-forward neural networks
by: Franco, Nicola Rares, et al.
Published: (2025)