Deep anomaly detection with deviation networks
Although deep learning has been applied to successfully address many data mining problems, relatively limited work has been done on deep learning for anomaly detection. Existing deep anomaly detection methods, which focus on learning new feature representations to enable downstream anomaly detection...
Saved in:
Main Authors: | PANG, Guansong, SHEN, Chunhua, HENGEL, Anton van den |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2019
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/7138 https://ink.library.smu.edu.sg/context/sis_research/article/8141/viewcontent/3292500.3330871.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Toward deep supervised anomaly detection: Reinforcement learning from partially labeled anomaly data
by: PANG, Guansong, et al.
Published: (2021) -
Deep learning for anomaly detection: Challenges, methods, and opportunities
by: PANG, Guansong, et al.
Published: (2021) -
Deep learning for anomaly detection: A review
by: PANG, Guansong, et al.
Published: (2022) -
Deep weakly-supervised anomaly detection
by: PANG, Guansong, et al.
Published: (2023) -
ROBUST AND ADAPTIVE ANOMALY DETECTION WITH DEEP LEARNING
by: ADAM DAVID GOODGE
Published: (2023)