RePAD: Real-time Proactive Anomaly Detection for Time Series

RePAD: Real-time Proactive Anomaly Detection for Time Series

24 January 2020

Ernst Gunnar Gran

Papers citing "RePAD: Real-time Proactive Anomaly Detection for Time Series"

11 / 11 papers shown

Title
Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-time Lightweight Time Series Anomaly Detection Ming-Chang Lee Jia-Chun Lin Sokratis K. Katsikas AI4TS 27 2 0 26 Jul 2024
Evaluation of k-means time series clustering based on z-normalization and NP-Free Ming-Chang Lee Jia-Chun Lin Volker Stolz AI4TS 33 0 0 28 Jan 2024
RoLA: A Real-Time Online Lightweight Anomaly Detection System for Multivariate Time Series Ming-Chang Lee Jia-Chun Lin AI4TS 27 7 0 25 May 2023
Impact of Deep Learning Libraries on Online Adaptive Lightweight Time Series Anomaly Detection Ming-Chang Lee Jia-Chun Lin AI4TS 22 2 0 30 Apr 2023
NP-Free: A Real-Time Normalization-free and Parameter-tuning-free Representation Approach for Open-ended Time Series Ming-Chang Lee Jia-Chun Lin Volker Stolz AI4TS 29 1 0 12 Apr 2023
RePAD2: Real-Time, Lightweight, and Adaptive Anomaly Detection for Open-Ended Time Series Ming-Chang Lee Jia-Chun Lin AI4TS 30 8 0 01 Mar 2023
Fraud Analytics: A Decade of Research -- Organizing Challenges and Solutions in the Field Christopher Bockel-Rickermann Tim Verdonck Wouter Verbeke 35 12 0 07 Dec 2022
SALAD: Self-Adaptive Lightweight Anomaly Detection for Real-time Recurrent Time Series Ming-Chang Lee Jia-Chun Lin Ernst Gunnar Gran AI4TS 40 13 0 19 Apr 2021
How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection? Ming-Chang Lee Jia-Chun Lin Ernst Gunnar Gran AI4TS 17 12 0 12 Feb 2021
ReRe: A Lightweight Real-time Ready-to-Go Anomaly Detection Approach for Time Series Ming-Chang Lee Jia-Chun Lin Ernst Gunnar Gran AI4TS 32 31 0 05 Apr 2020
DALC: Distributed Automatic LSTM Customization for Fine-Grained Traffic Speed Prediction Ming-Chang Lee Jia-Chun Lin AI4TS 6 6 0 24 Jan 2020