Mitigating Out-of-Distribution Data Density Overestimation in Energy-Based Models

30 May 2022

Papers citing "Mitigating Out-of-Distribution Data Density Overestimation in Energy-Based Models"

17 / 17 papers shown

Title
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 239 30,108 0 01 Mar 2022
JEM++: Improved Techniques for Training JEM Xiulong Yang Shihao Ji AAML VLM 50 30 0 19 Sep 2021
On Out-of-distribution Detection with Energy-based Models Sven Elflein Bertrand Charpentier Daniel Zügner Stephan Günnemann OODD 57 19 0 03 Jul 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 64 256 0 09 Jan 2021
Multiscale Score Matching for Out-of-Distribution Detection Ahsan Mahmood Junier Oliva M. Styner OODD 145 30 0 25 Oct 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 78 542 0 06 Dec 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 136 276 0 25 Sep 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 213 3,870 0 12 Jul 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 174 720 0 07 Jun 2019
On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models Erik Nijkamp Mitch Hill Tian Han Song-Chun Zhu Ying Nian Wu 51 154 0 29 Mar 2019
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 173 1,476 0 11 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 57 756 0 22 Oct 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 279 3,124 0 09 Jul 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 256 8,876 0 25 Aug 2017
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications Tim Salimans A. Karpathy Xi Chen Diederik P. Kingma 91 939 0 19 Jan 2017
Theoretical guarantees for approximate sampling from smooth and log-concave densities A. Dalalyan 66 514 0 23 Dec 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 426 16,944 0 20 Dec 2013