Explainable Deep One-Class Classification

3 July 2020

Philipp Liznerski

Lukas Ruff

Robert A. Vandermeulen

Papers citing "Explainable Deep One-Class Classification"

37 / 37 papers shown

Title
Detection of Aerial Spoofing Attacks to LEO Satellite Systems via Deep Learning Jos Wigchert Savio Sciancalepore Gabriele Oligeri 95 0 0 20 Dec 2024
A Unifying Review of Deep and Shallow Anomaly Detection Lukas Ruff Jacob R. Kauffmann Robert A. Vandermeulen G. Montavon Wojciech Samek Marius Kloft Thomas G. Dietterich Klaus-Robert Muller UQCV 64 790 0 24 Sep 2020
Encoding Structure-Texture Relation with P-Net for Anomaly Detection in Retinal Images Kang Zhou Yuting Xiao Jianlong Yang Jun Cheng Wen Liu Weixin Luo Zaiwang Gu Jiang-Dong Liu Shenghua Gao MedIm 69 117 0 09 Aug 2020
Fairwashing Explanations with Off-Manifold Detergent Christopher J. Anders Plamen Pasliev Ann-Kathrin Dombrowski K. Müller Pan Kessel FAtt FaML 42 96 0 20 Jul 2020
Rethinking Assumptions in Deep Anomaly Detection Lukas Ruff Robert A. Vandermeulen Billy Joe Franks Klaus-Robert Muller Marius Kloft 61 89 0 30 May 2020
Classification-Based Anomaly Detection for General Data Liron Bergman Yedid Hoshen 47 348 0 05 May 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 101 82 0 17 Mar 2020
DROCC: Deep Robust One-Class Classification Sachin Goyal Aditi Raghunathan Moksh Jain H. Simhadri Prateek Jain VLM 57 163 0 28 Feb 2020
Iterative energy-based projection on a normal data manifold for anomaly localization David Dehaene Oriel Frigo Sébastien Combrexelle P. Eline 32 145 0 10 Feb 2020
Attribute Restoration Framework for Anomaly Detection Chaoqin Huang Fei Ye Jinkun Cao Maosen Li Ya Zhang Cewu Lu 91 49 0 25 Nov 2019
Attention Guided Anomaly Localization in Images Shashanka Venkataramanan Kuan-Chuan Peng Rajat Vikram Singh Abhijit Mahalanobis 48 22 0 19 Nov 2019
Towards Visually Explaining Variational Autoencoders Wenqian Liu Runze Li Meng Zheng Srikrishna Karanam Ziyan Wu B. Bhanu Richard J. Radke Mario Sznaier 84 217 0 18 Nov 2019
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty Dan Hendrycks Mantas Mazeika Saurav Kadavath D. Song OOD SSL 47 940 0 28 Jun 2019
Deep Semi-Supervised Anomaly Detection Lukas Ruff Robert A. Vandermeulen Nico Görnitz Alexander Binder Emmanuel Müller K. Müller Marius Kloft UQCV 47 543 0 06 Jun 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 78 1,005 0 26 Feb 2019
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 143 1,468 0 11 Dec 2018
Deep Anomaly Detection Using Geometric Transformations I. Golan Ran El-Yaniv 71 603 0 28 May 2018
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models Jacob R. Kauffmann K. Müller G. Montavon DRL 67 96 0 16 May 2018
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks Agrim Gupta Justin Johnson Li Fei-Fei Silvio Savarese Alexandre Alahi GAN 151 1,895 0 29 Mar 2018
Anomaly Detection using One-Class Neural Networks Raghavendra Chalapathy A. Menon Sanjay Chawla UQCV 48 395 0 18 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 211 8,807 0 25 Aug 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 276 2,254 0 24 Jun 2017
Safe Model-based Reinforcement Learning with Stability Guarantees Felix Berkenkamp M. Turchetta Angela P. Schoellig Andreas Krause 141 845 0 23 May 2017
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery T. Schlegl Philipp Seeböck S. Waldstein U. Schmidt-Erfurth Georg Langs MedIm GAN 73 2,219 0 17 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 149 5,920 0 04 Mar 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 297 1,849 0 03 Feb 2017
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks Wenjie Luo Yujia Li R. Urtasun R. Zemel HAI 79 1,789 0 15 Jan 2017
Deep-Anomaly: Fully Convolutional Neural Network for Fast Anomaly Detection in Crowded Scenes Mohammad Sabokrou Mohsen Fayyaz Mahmood Fathy Zahra Moayed Reinhard Klette 69 430 0 03 Sep 2016
Fully Convolutional Networks for Semantic Segmentation Evan Shelhamer Jonathan Long Trevor Darrell VOS SSeg 422 37,704 0 20 May 2016
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Shcherbina A. Kundaje FAtt 74 782 0 05 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 772 16,828 0 16 Feb 2016
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks Sebastian Bach Alexander Binder G. Montavon K. Müller Wojciech Samek 76 199 0 01 Dec 2015
You Only Look Once: Unified, Real-Time Object Detection Joseph Redmon S. Divvala Ross B. Girshick Ali Farhadi ObjD 616 36,643 0 08 Jun 2015
Learning Deconvolution Network for Semantic Segmentation Hyeonwoo Noh Seunghoon Hong Bohyung Han SSeg 191 4,166 0 17 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.2K 149,474 0 22 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.1K 99,991 0 04 Sep 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 219 7,252 0 20 Dec 2013