Out-of-Distribution Detection with Reconstruction Error and Typicality-based Penalty

24 December 2022

Papers citing "Out-of-Distribution Detection with Reconstruction Error and Typicality-based Penalty"

50 / 61 papers shown

Title
Model-agnostic out-of-distribution detection using combined statistical tests Federico Bergamin Pierre-Alexandre Mattei Jakob Drachmann Havtorn Hugo Senetaire Hugo Schmutz Lars Maaløe Søren Hauberg J. Frellsen OODD 71 19 0 02 Mar 2022
Generalized Out-of-Distribution Detection: A Survey Jingkang Yang Kaiyang Zhou Yixuan Li Ziwei Liu 301 943 0 21 Oct 2021
On the expressivity of bi-Lipschitz normalizing flows Alexandre Verine Benjamin Négrevergne F. Rossi Y. Chevaleyre TPM 79 17 0 15 Jul 2021
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models Lily H. Zhang Mark Goldstein Rajesh Ranganath OODD 177 106 0 14 Jul 2021
The Dimpled Manifold Model of Adversarial Examples in Machine Learning A. Shamir Odelia Melamed Oriel BenShmuel AAML 70 50 0 18 Jun 2021
Improved Autoregressive Modeling with Distribution Smoothing Chenlin Meng Jiaming Song Yang Song Shengjia Zhao Stefano Ermon DiffM 66 23 0 28 Mar 2021
Implicit Normalizing Flows Cheng Lu Jianfei Chen Chongxuan Li Qiuhao Wang Jun Zhu AI4CE 54 34 0 17 Mar 2021
Regularization with Latent Space Virtual Adversarial Training Genki Osada Budrul Ahsan Revoti Prasad Bora Takashi Nishide 78 14 0 26 Nov 2020
Further Analysis of Outlier Detection with Deep Generative Models Ziyu Wang Bin Dai David Wipf Jun Zhu 69 40 0 25 Oct 2020
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 135 805 0 24 Sep 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Wang Roger C. Grosse J. Jacobsen 56 94 0 16 Jun 2020
Density of States Estimation for Out-of-Distribution Detection Warren Morningstar Cusuh Ham Andrew Gallagher Balaji Lakshminarayanan Alexander A. Alemi Joshua V. Dillon OODD 87 85 0 16 Jun 2020
Learning disconnected manifolds: a no GANs land Ugo Tanielian Thibaut Issenhuth Elvis Dohmatob Jérémie Mary 49 36 0 08 Jun 2020
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder Zhisheng Xiao Qing Yan Y. Amit OODD 167 195 0 06 Mar 2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data Yen-Chang Hsu Yilin Shen Hongxia Jin Z. Kira OODD 109 577 0 26 Feb 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 544 10,591 0 17 Feb 2020
Input complexity and out-of-distribution detection with likelihood-based generative models Joan Serrà David Álvarez Vicencc Gómez Olga Slizovskaia José F. Núñez Jordi Luque OODD 157 277 0 25 Sep 2019
Unsupervised Out-of-Distribution Detection by Maximum Classifier Discrepancy Qing Yu Kiyoharu Aizawa OODD 60 168 0 14 Aug 2019
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 212 728 0 07 Jun 2019
A RAD approach to deep mixture models Laurent Dinh Jascha Narain Sohl-Dickstein Hugo Larochelle Razvan Pascanu 67 46 0 18 Mar 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 66 175 0 13 Feb 2019
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 183 1,487 0 11 Dec 2018
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 272 284 0 03 Dec 2018
Do Deep Generative Models Know What They Don't Know? Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan OOD 87 759 0 22 Oct 2018
Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers Apoorv Vyas Nataraj Jammalamadaka Xia Zhu Dipankar Das Bharat Kaul Theodore L. Willke OODD 78 247 0 04 Sep 2018
IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis Huaibo Huang Zhihang Li Ran He Zhenan Sun Tieniu Tan DRL 53 266 0 17 Jul 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 199 2,063 0 10 Jul 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 305 3,144 0 09 Jul 2018
Generative Probabilistic Novelty Detection with Adversarial Autoencoders Stanislav Pidhorskyi Ranya Almohsen Donald Adjeroh Gianfranco Doretto UQCV 61 323 0 06 Jul 2018
Latent Space Autoregression for Novelty Detection Davide Abati Angelo Porrello Simone Calderara Rita Cucchiara 122 435 0 04 Jul 2018
Assessing Generative Models via Precision and Recall Mehdi S. M. Sajjadi Olivier Bachem Mario Lucic Olivier Bousquet Sylvain Gelly EGVM 97 584 0 31 May 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 88 531 0 28 May 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 86 1,179 0 17 May 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 249 3,194 0 01 Feb 2018
The Robust Manifold Defense: Adversarial Training using Generative Models A. Jalal Andrew Ilyas C. Daskalakis A. Dimakis AAML 99 174 0 26 Dec 2017
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples Yang Song Taesup Kim Sebastian Nowozin Stefano Ermon Nate Kushman AAML 126 790 0 30 Oct 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 163 2,160 0 21 Aug 2017
The Reversible Residual Network: Backpropagation Without Storing Activations Aidan Gomez Mengye Ren R. Urtasun Roger C. Grosse 79 551 0 14 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 319 12,151 0 19 Jun 2017
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks Shiyu Liang Yixuan Li R. Srikant UQCV OODD 171 2,082 0 08 Jun 2017
MagNet: a Two-Pronged Defense against Adversarial Examples Dongyu Meng Hao Chen AAML 56 1,208 0 25 May 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 105 894 0 01 Mar 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 179 3,480 0 07 Oct 2016
A Boundary Tilting Persepective on the Phenomenon of Adversarial Examples T. Tanay Lewis D. Griffin AAML 103 272 0 27 Aug 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 282 8,587 0 16 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 547 5,912 0 08 Jul 2016
Conditional Image Generation with PixelCNN Decoders Aaron van den Oord Nal Kalchbrenner Oriol Vinyals L. Espeholt Alex Graves Koray Kavukcuoglu VLM 226 2,519 0 16 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 277 3,722 0 26 May 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 356 8,002 0 23 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,510 0 10 Dec 2015