Clustering and Unsupervised Anomaly Detection with L2 Normalized Deep Auto-Encoder Representations

1 February 2018

Papers citing "Clustering and Unsupervised Anomaly Detection with L2 Normalized Deep Auto-Encoder Representations"

11 / 11 papers shown

Title
FaaSched: A Jitter-Aware Serverless Scheduler Abhisek Panda S. Sarangi 39 0 0 11 Mar 2023
Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection Shaoshen Wang Yanbin Liu Ling Chen Chengqi Zhang 24 0 0 29 May 2022
on the effectiveness of generative adversarial network on anomaly detection Laya Rafiee T. Fevens 28 5 0 31 Dec 2021
Student-Teacher Feature Pyramid Matching for Anomaly Detection Guodong Wang Shumin Han Errui Ding Di Huang 23 214 0 07 Mar 2021
Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation Mehdi Bahri Eimear O' Sullivan Shunwang Gong Feng Liu Xiaoming Liu M. Bronstein S. Zafeiriou CVBM 3DH 29 16 0 16 Dec 2020
Cold-start Active Learning through Self-supervised Language Modeling Michelle Yuan Hsuan-Tien Lin Jordan L. Boyd-Graber 116 180 0 19 Oct 2020
Conditional Gaussian Distribution Learning for Open Set Recognition Xin Sun Zhen Yang Chi Zhang Guohao Peng K. Ling BDL UQCV 157 217 0 19 Mar 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 26 21 0 26 Feb 2020
Unsupervised Contextual Anomaly Detection using Joint Deep Variational Generative Models Yaniv Shulman DRL 21 6 0 01 Apr 2019
Deep Learning for Anomaly Detection: A Survey Raghavendra Chalapathy Sanjay Chawla AI4TS 41 1,479 0 10 Jan 2019
Rare Event Detection using Disentangled Representation Learning Ryuhei Hamaguchi Ken Sakurada Ryosuke Nakamura DRL 20 35 0 04 Dec 2018