ARAE: Adversarially Robust Training of Autoencoders Improves Novelty Detection

12 March 2020

Papers citing "ARAE: Adversarially Robust Training of Autoencoders Improves Novelty Detection"

4 / 4 papers shown

Title
Managing the unknown: a survey on Open Set Recognition and tangential areas Marcos Barcina-Blanco J. Lobo Pablo Garcia-Bringas Javier Del Ser VLM 27 2 0 14 Dec 2023
GRAM: An Interpretable Approach for Graph Anomaly Detection using Gradient Attention Maps Yifei Yang Peng Wang Xiaofan He Dongmian Zou 14 5 0 10 Nov 2023
Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly Detection Gaoang Wang Yibing Zhan Xinchao Wang Min-Gyoo Song K. Nahrstedt 24 11 0 24 Jul 2022
Data Invariants to Understand Unsupervised Out-of-Distribution Detection Lars Doorenbos Raphael Sznitman Pablo Márquez-Neila OODD 21 6 0 26 Nov 2021