DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN

23 August 2018

Papers citing "DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN"

22 / 22 papers shown

Title
PerSival: Neural-network-based visualisation for pervasive continuum-mechanical simulations in musculoskeletal biomechanics D. Rosin Johannes Kässinger Xingyao Yu Okan Avci C. Bleiler Oliver Röhrle 3DH AI4CE 21 1 0 07 Dec 2023
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation Shuang Zhou Xiao Shi Huang Ninghao Liu Huachi Zhou F. Chung Longhai Huang 49 23 0 18 Jun 2023
Towards Diverse and Coherent Augmentation for Time-Series Forecasting Xiyuan Zhang Ranak Roy Chowdhury Jingbo Shang Rajesh K. Gupta Dezhi Hong AI4TS 32 4 0 24 Mar 2023
Fair Generative Models via Transfer Learning Christopher T. H. Teo Milad Abdollahzadeh Ngai-man Cheung 21 24 0 02 Dec 2022
Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing? Keshigeyan Chandrasegaran Ngoc-Trung Tran Yunqing Zhao Ngai-man Cheung 93 41 0 29 Jun 2022
Multi-scale Anomaly Detection for Big Time Series of Industrial Sensors Quan-Xin Ding Shenghua Liu Bin Zhou Huawei Shen Xueqi Cheng AI4TS AI4CE 24 1 0 18 Apr 2022
Machine Learning in NextG Networks via Generative Adversarial Networks E. Ayanoglu Kemal Davaslioglu Y. Sagduyu GAN 24 34 0 09 Mar 2022
Federated Variational Learning for Anomaly Detection in Multivariate Time Series Kai Zhang Yushan Jiang Lee M. Seversky Chengtao Xu Dahai Liu Haoze Song AI4TS 14 26 0 18 Aug 2021
Synthesising Multi-Modal Minority Samples for Tabular Data Sajad Darabi Yotam Elor 21 10 0 17 May 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder Clément Chadebec Elina Thibeau-Sutre Ninon Burgos S. Allassonnière 48 63 0 30 Apr 2021
A Survey on Industrial Control System Testbeds and Datasets for Security Research Mauro Conti Denis Donadel Federico Turrin 16 137 0 10 Feb 2021
SAG-GAN: Semi-Supervised Attention-Guided GANs for Data Augmentation on Medical Images Chang Qi Junyang Chen Guizhi Xu Zhenghua Xu Thomas Lukasiewicz Yang Liu GAN MedIm 16 13 0 15 Nov 2020
G2D: Generate to Detect Anomaly M. PourReza Bahram Mohammadi Mostafa Khaki Samir Bouindour H. Snoussi Mohammad Sabokrou 16 60 0 20 Jun 2020
Time Series Data Augmentation for Deep Learning: A Survey Qingsong Wen Liang Sun Fan Yang Xiaomin Song Jing Gao Xue Wang Huan Xu AI4TS 32 636 0 27 Feb 2020
Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game Ngoc-Trung Tran Viet-Hung Tran Ngoc-Bao Nguyen Linxiao Yang Ngai-man Cheung SSL GAN 23 60 0 16 Nov 2019
A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification Varun Kumar Hadrien Glaude Cyprien de Lichy William Campbell 26 83 0 09 Oct 2019
Exploring Bias in GAN-based Data Augmentation for Small Samples Mengxiao Hu Jinlong Li 16 20 0 21 May 2019
Fence GAN: Towards Better Anomaly Detection Cuong Phuc Ngo Amadeus Aristo Winarto C. Kou Sojeong Park Farhan Akram H. Lee 23 93 0 02 Apr 2019
A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series Wenqian Jiang Cheng Cheng Beitong Zhou Guijun Ma Ye Yuan AI4CE 29 128 0 01 Apr 2019
Deep Learning for Anomaly Detection: A Survey Raghavendra Chalapathy Sanjay Chawla AI4TS 41 1,479 0 10 Jan 2019
AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation Masataka Yamaguchi Yuma Koizumi Noboru Harada 22 37 0 14 Dec 2018
RenderGAN: Generating Realistic Labeled Data Leon Sixt Benjamin Wild Tim Landgraf GAN 170 176 0 04 Nov 2016