FedTADBench: Federated Time-Series Anomaly Detection Benchmark

FedTADBench: Federated Time-Series Anomaly Detection Benchmark

19 December 2022

Le Zhang

Papers citing "FedTADBench: Federated Time-Series Anomaly Detection Benchmark"

7 / 7 papers shown

Title
Federated Learning with Reservoir State Analysis for Time Series Anomaly Detection Keigo Nogami Tamura Hiroto Gouhei Tanaka FedML 80 0 0 17 Feb 2025
From Dense to Sparse: Event Response for Enhanced Residential Load Forecasting Xin Cao Qinghua Tao Yingjie Zhou Lu Zhang Le Zhang Dongjin Song Dapeng Oliver Wu Ce Zhu 25 0 0 06 Jan 2025
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection Ronghui Xu Hao Miao Senzhang Wang Philip S. Yu Jianxin Wang AI4TS 40 12 0 04 Jun 2024
ADGym: Design Choices for Deep Anomaly Detection Minqi Jiang Chaochuan Hou Ao Zheng Songqiao Han Hailiang Huang Qingsong Wen Xiyang Hu Yue Zhao 11 14 0 27 Sep 2023
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series Astha Garg Wenyu Zhang Jules Samaran R. Savitha Chuan-Sheng Foo AI4TS 27 221 0 23 Sep 2021
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection Yingjie Zhou Xuchen Song Yanru Zhang Fanxing Liu Ce Zhu Lingqiao Liu UQCV 20 102 0 22 May 2021
Anomaly Detection of Time Series with Smoothness-Inducing Sequential Variational Auto-Encoder Longyuan Li Junchi Yan Haiyang Wang Yaohui Jin BDL AI4TS 35 134 0 02 Feb 2021