Perfect density models cannot guarantee anomaly detection

7 December 2020

Papers citing "Perfect density models cannot guarantee anomaly detection"

50 / 56 papers shown

Title
A Survey on Diffusion Models for Anomaly Detection Qingbin Liu Zhenchao Ma Zepu Wang Yang Liu Zehua Wang Peng Sun Liang Song Bo Hu Azzedine Boukerche Victor C.M. Leung DiffM MedIm 67 5 0 20 Jan 2025
AI and the Everything in the Whole Wide World Benchmark Inioluwa Deborah Raji Emily M. Bender Amandalynne Paullada Emily L. Denton A. Hanna 77 305 0 26 Nov 2021
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models Lily H. Zhang Mark Goldstein Rajesh Ranganath OODD 167 105 0 14 Jul 2021
Data and its (dis)contents: A survey of dataset development and use in machine learning research Amandalynne Paullada Inioluwa Deborah Raji Emily M. Bender Emily L. Denton A. Hanna 111 524 0 09 Dec 2020
Further Analysis of Outlier Detection with Deep Generative Models Ziyu Wang Bin Dai David Wipf Jun Zhu 53 39 0 25 Oct 2020
Energy-based Out-of-distribution Detection Weitang Liu Xiaoyun Wang John Douglas Owens Yixuan Li OODD 271 1,355 0 08 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 106 797 0 24 Sep 2020
Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows Marco Rudolph Bastian Wandt Bodo Rosenhahn UQCV 44 329 0 28 Aug 2020
Reparametrization Invariance in non-parametric Causal Discovery Martin Jørgensen Søren Hauberg CML 23 1 0 12 Aug 2020
Hybrid Discriminative-Generative Training via Contrastive Learning Hao Liu Pieter Abbeel SSL 70 40 0 17 Jul 2020
Contrastive Training for Improved Out-of-Distribution Detection Jim Winkens Rudy Bunel Abhijit Guha Roy Robert Stanforth Vivek Natarajan ... Alan Karthikesalingam Simon A. A. Kohl taylan. cemgil S. M. Ali Eslami Olaf Ronneberger OODD 123 241 0 10 Jul 2020
NVAE: A Deep Hierarchical Variational Autoencoder Arash Vahdat Jan Kautz BDL 69 910 0 08 Jul 2020
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? Angelos Filos P. Tigas R. McAllister Nicholas Rhinehart Sergey Levine Y. Gal 56 187 0 26 Jun 2020
Large image datasets: A pyrrhic win for computer vision? Vinay Uday Prabhu Abeba Birhane 61 366 0 24 Jun 2020
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features R. Schirrmeister Yuxuan Zhou T. Ball Dan Zhang UQCV 57 88 0 18 Jun 2020
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 149 14,953 0 18 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Wang Roger C. Grosse J. Jacobsen 42 93 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 74 84 0 16 Jun 2020
Why Normalizing Flows Fail to Detect Out-of-Distribution Data Polina Kirichenko Pavel Izmailov A. Wilson OODD 83 275 0 15 Jun 2020
Hybrid Models for Open Set Recognition Hongjie Zhang Ang Li Jie Guo Yanwen Guo BDL 127 185 0 27 Mar 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 78 543 0 06 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 202 1,691 0 05 Dec 2019
Deep Generative Models Strike Back! Improving Understanding and Evaluation in Light of Unmet Expectations for OoD Data John Just Sambuddha Ghosal DiffM DRL 60 6 0 12 Nov 2019
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 144 276 0 25 Sep 2019
Neural Machine Translation with Byte-Level Subwords Changhan Wang Kyunghyun Cho Jiatao Gu 79 178 0 07 Sep 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 182 722 0 07 Jun 2019
Does Object Recognition Work for Everyone? Terrance Devries Ishan Misra Changhan Wang Laurens van der Maaten 95 265 0 06 Jun 2019
Understanding the Limitations of Conditional Generative Models Ethan Fetaya J. Jacobsen Will Grathwohl R. Zemel 66 53 0 04 Jun 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 170 3,431 0 28 Mar 2019
Curiosity-Driven Experience Prioritization via Density Estimation Rui Zhao Volker Tresp 102 54 0 20 Feb 2019
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design Jonathan Ho Xi Chen A. Srinivas Yan Duan Pieter Abbeel DRL 82 449 0 01 Feb 2019
Understanding the (un)interpretability of natural image distributions using generative models Ryen Krusinga Sohil Shah Matthias Zwicker Tom Goldstein David Jacobs DiffM FAtt GAN 56 11 0 06 Jan 2019
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 181 1,478 0 11 Dec 2018
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 115 1,466 0 29 Nov 2018
Do Deep Generative Models Know What They Don't Know? Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan OOD 63 757 0 22 Oct 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 185 2,050 0 10 Jul 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 290 3,129 0 09 Jul 2018
Image Transformer Niki Parmar Ashish Vaswani Jakob Uszkoreit Lukasz Kaiser Noam M. Shazeer Alexander Ku Dustin Tran ViT 133 1,679 0 15 Feb 2018
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 121 1,857 0 20 May 2017
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning Justin Fu John D. Co-Reyes Sergey Levine OffRL 52 155 0 03 Mar 2017
Conditional Image Generation with PixelCNN Decoders Aaron van den Oord Nal Kalchbrenner Oriol Vinyals L. Espeholt Alex Graves Koray Kavukcuoglu VLM 204 2,511 0 16 Jun 2016
Unifying Count-Based Exploration and Intrinsic Motivation Marc G. Bellemare S. Srinivasan Georg Ostrovski Tom Schaul D. Saxton Rémi Munos 167 1,478 0 06 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 263 78 0 26 May 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 466 2,568 0 25 Jan 2016
A note on the evaluation of generative models Lucas Theis Aaron van den Oord Matthias Bethge EGVM 123 1,145 0 05 Nov 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 310 4,179 0 21 May 2015
Crypto-Nets: Neural Networks over Encrypted Data P. Xie Mikhail Bilenko Tom Finley Ran Gilad-Bachrach Kristin E. Lauter M. Naehrig FedML 83 150 0 18 Dec 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 121 2,258 0 30 Oct 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 460 43,649 0 17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,348 0 04 Sep 2014