Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One

6 December 2019

Will Grathwohl

Kuan-Chieh Jackson Wang

Papers citing "Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One"

50 / 360 papers shown

Title
Learning Energy-Based Models With Adversarial Training Xuwang Yin Shiying Li Gustavo K. Rohde AAML DiffM 33 9 0 11 Dec 2020
Composite Adversarial Attacks Xiaofeng Mao YueFeng Chen Shuhui Wang Hang Su Yuan He Hui Xue AAML 30 47 0 10 Dec 2020
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection Dennis Ulmer Giovanni Cina OODD 32 31 0 09 Dec 2020
Accurate 3D Object Detection using Energy-Based Models Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon 3DPC 35 10 0 08 Dec 2020
Deep Energy-Based NARX Models J. Hendriks Fredrik K. Gustafsson Antônio H. Ribeiro A. Wills Thomas B. Schon 17 10 0 08 Dec 2020
Perfect density models cannot guarantee anomaly detection Charline Le Lan Laurent Dinh 30 49 0 07 Dec 2020
Contrastive Divergence Learning is a Time Reversal Adversarial Game Omer Yair T. Michaeli GAN 18 6 0 06 Dec 2020
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization Kien Do T. Tran Svetha Venkatesh BDL 14 3 0 03 Dec 2020
Improved Contrastive Divergence Training of Energy Based Models Yilun Du Shuang Li J. Tenenbaum Igor Mordatch 39 138 0 02 Dec 2020
Energy-Based Models for Continual Learning Shuang Li Yilun Du Gido M. van de Ven Igor Mordatch 27 42 0 24 Nov 2020
Dense open-set recognition with synthetic outliers generated by Real NVP Matej Grcić Petra Bevandić Sinisa Segvic 8 40 0 22 Nov 2020
Multiscale Score Matching for Out-of-Distribution Detection Ahsan Mahmood Junier Oliva M. Styner OODD 6 30 0 25 Oct 2020
Further Analysis of Outlier Detection with Deep Generative Models Ziyu Wang Bin Dai David Wipf Jun Zhu 14 39 0 25 Oct 2020
Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling Bo Pang Erik Nijkamp Jiali Cui Tian Han Ying Nian Wu SSL 32 4 0 19 Oct 2020
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models Fan Bao Kun Xu Chongxuan Li Lanqing Hong Jun Zhu Bo Zhang DiffM 22 8 0 16 Oct 2020
Bi-level Score Matching for Learning Energy-based Latent Variable Models Fan Bao Chongxuan Li Kun Xu Hang Su Jun Zhu Bo Zhang 24 13 0 15 Oct 2020
No MCMC for me: Amortized sampling for fast and stable training of energy-based models Will Grathwohl Jacob Kelly Milad Hashemi Mohammad Norouzi Kevin Swersky David Duvenaud 11 70 0 08 Oct 2020
Set Prediction without Imposing Structure as Conditional Density Estimation David W. Zhang Gertjan J. Burghouts Cees G. M. Snoek 48 17 0 08 Oct 2020
Energy-based Out-of-distribution Detection Weitang Liu Xiaoyun Wang John Douglas Owens Yixuan Li OODD 71 1,290 0 08 Oct 2020
A Neural Network MCMC sampler that maximizes Proposal Entropy Zengyi Li Yubei Chen Friedrich T. Sommer 25 14 0 07 Oct 2020
Conditional Generative Modeling via Learning the Latent Space Sameera Ramasinghe Kanchana Ranasinghe Salman Khan Nick Barnes Stephen Gould BDL 31 9 0 07 Oct 2020
Generative Model-Enhanced Human Motion Prediction Anthony Bourached Ryan-Rhys Griffiths Robert J. Gray A. Jha P. Nachev 26 15 0 05 Oct 2020
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models Zhisheng Xiao Karsten Kreis Jan Kautz Arash Vahdat 16 123 0 01 Oct 2020
Iterative Reconstruction for Low-Dose CT using Deep Gradient Priors of Generative Model Zhuonan He Yikun Zhang Yu Guan S. Niu Yi Zhang Yang Chen Qiegen Liu DiffM MedIm 30 12 0 27 Sep 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 20 779 0 24 Sep 2020
Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings John Mitros A. Pakrashi Brian Mac Namee UQCV 26 2 0 03 Sep 2020
Likelihood Landscapes: A Unifying Principle Behind Many Adversarial Defenses Fu-Huei Lin Rohit Mittapalli Prithvijit Chattopadhyay Daniel Bolya Judy Hoffman AAML 46 2 0 25 Aug 2020
Generative Classifiers as a Basis for Trustworthy Image Classification Radek Mackowiak Lynton Ardizzone Ullrich Kothe Carsten Rother 14 4 0 29 Jul 2020
Hybrid Discriminative-Generative Training via Contrastive Learning Hao Liu Pieter Abbeel SSL 20 40 0 17 Jul 2020
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances Jihoon Tack Sangwoo Mo Jongheon Jeong Jinwoo Shin OODD 11 588 0 16 Jul 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching Tianyu Pang Kun Xu Chongxuan Li Yang Song Stefano Ermon Jun Zhu DiffM 31 53 0 07 Jul 2020
Kernel Stein Generative Modeling Wei-Cheng Chang Chun-Liang Li Youssef Mroueh Yiming Yang DiffM BDL 33 5 0 06 Jul 2020
Supermasks in Superposition Mitchell Wortsman Vivek Ramanujan Rosanne Liu Aniruddha Kembhavi Mohammad Rastegari J. Yosinski Ali Farhadi SSL CLL 19 279 0 26 Jun 2020
Strictly Batch Imitation Learning by Energy-based Distribution Matching Daniel Jarrett Ioana Bica M. Schaar OffRL 13 62 0 25 Jun 2020
Telescoping Density-Ratio Estimation Benjamin Rhodes Kai Xu Michael U. Gutmann 25 94 0 22 Jun 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 118 16,947 0 19 Jun 2020
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features R. Schirrmeister Yuxuan Zhou T. Ball Dan Zhang UQCV 6 88 0 18 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 25 169 0 16 Jun 2020
Rethinking the Role of Gradient-Based Attribution Methods for Model Interpretability Suraj Srinivas F. Fleuret FAtt 13 1 0 16 Jun 2020
Exponential Tilting of Generative Models: Improving Sample Quality by Training and Sampling from Latent Energy Zhisheng Xiao Qing Yan Y. Amit DRL 8 8 0 15 Jun 2020
Revisiting Explicit Regularization in Neural Networks for Well-Calibrated Predictive Uncertainty Taejong Joo U. Chung BDL UQCV 6 0 0 11 Jun 2020
EDropout: Energy-Based Dropout and Pruning of Deep Neural Networks Hojjat Salehinejad S. Valaee 8 44 0 07 Jun 2020
A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning Sameer Khurana Antoine Laurent Wei-Ning Hsu J. Chorowski A. Lancucki R. Marxer James R. Glass SSL BDL 14 29 0 03 Jun 2020
Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based Models Mitch Hill Jonathan Mitchell Song-Chun Zhu AAML 16 68 0 27 May 2020
Lifted Regression/Reconstruction Networks R. Høier Christopher Zach 16 7 0 07 May 2020
How to Train Your Energy-Based Model for Regression Fredrik K. Gustafsson Martin Danelljan Radu Timofte Thomas B. Schon 40 42 0 04 May 2020
Protecting Classifiers From Attacks. A Bayesian Approach Víctor Gallego Roi Naveiro A. Redondo D. Insua Fabrizio Ruggeri AAML 11 2 0 18 Apr 2020
Compositional Visual Generation and Inference with Energy Based Models Yilun Du Shuang Li Igor Mordatch CoGe 19 23 0 13 Apr 2020
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator Yuxuan Song Qiwei Ye Minkai Xu Tie-Yan Liu 19 8 0 05 Apr 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 98 0 20 Mar 2020