Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz
Discriminators

Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators

26 May 2019

Guy Wolf

Smita Krishnaswamy

Papers citing "Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators"

8 / 8 papers shown

Title
OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations Pramuditha Perera Ramesh Nallapati Bing Xiang 110 526 0 20 Mar 2019
Deep Learning for Anomaly Detection: A Survey Raghavendra Chalapathy Sanjay Chawla AI4TS 154 1,494 0 10 Jan 2019
Generative Probabilistic Novelty Detection with Adversarial Autoencoders Stanislav Pidhorskyi Ranya Almohsen Donald Adjeroh Gianfranco Doretto UQCV 40 321 0 06 Jul 2018
Latent Space Autoregression for Novelty Detection Davide Abati Angelo Porrello Simone Calderara Rita Cucchiara 100 434 0 04 Jul 2018
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 197 9,545 0 31 Mar 2017
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 478 9,044 0 10 Jun 2016
Asynchrony begets Momentum, with an Application to Deep Learning Jeff Donahue Philipp Krahenbuhl Stefan Hadjis Christopher Ré 92 141 0 31 May 2016
Adversarial Autoencoders Alireza Makhzani Jonathon Shlens Navdeep Jaitly Ian Goodfellow Brendan J. Frey GAN 86 2,224 0 18 Nov 2015