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
Adversarial Unlearning: Reducing Confidence Along Adversarial Directions Amrith Rajagopal Setlur Benjamin Eysenbach Virginia Smith Sergey Levine 14 18 0 03 Jun 2022
Guided Diffusion Model for Adversarial Purification Jinyi Wang Zhaoyang Lyu Dahua Lin Bo Dai Hongfei Fu DiffM 196 82 0 30 May 2022
Mitigating Out-of-Distribution Data Density Overestimation in Energy-Based Models Beomsu Kim Jong Chul Ye 11 1 0 30 May 2022
EBM Life Cycle: MCMC Strategies for Synthesis, Defense, and Density Modeling Mitch Hill Jonathan Mitchell Chu Chen Yuan Du M. Shah Song-Chun Zhu 14 0 0 24 May 2022
Diffusion Models for Adversarial Purification Weili Nie Brandon Guo Yujia Huang Chaowei Xiao Arash Vahdat Anima Anandkumar WIGM 200 418 0 16 May 2022
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model Jianwen Xie Y. Zhu Juntao Li Ping Li 24 50 0 13 May 2022
Energy-based Latent Aligner for Incremental Learning K. J. Joseph Salman Khan F. Khan Rao Muhammad Anwer V. Balasubramanian CLL 33 46 0 28 Mar 2022
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training Yifei Wang Yisen Wang Jiansheng Yang Zhouchen Lin AAML 26 13 0 25 Mar 2022
Mix and Match: Learning-free Controllable Text Generation using Energy Language Models Fatemehsadat Mireshghallah Kartik Goyal Taylor Berg-Kirkpatrick 36 78 0 24 Mar 2022
Bi-level Doubly Variational Learning for Energy-based Latent Variable Models Ge Kan Jinhu Lu Tian Wang Baochang Zhang Aichun Zhu Lei Huang Guodong Guo H. Snoussi 25 6 0 24 Mar 2022
Out of Distribution Detection, Generalization, and Robustness Triangle with Maximum Probability Theorem Amir Emad Marvasti Ehsan Emad Marvasti Ulas Bagci OOD 24 0 0 23 Mar 2022
No Shifted Augmentations (NSA): compact distributions for robust self-supervised Anomaly Detection Mohamed Yousef Marcel R. Ackermann Unmesh Kurup Tom E. Bishop OODD OOD 40 3 0 19 Mar 2022
Defending Black-box Skeleton-based Human Activity Classifiers He-Nan Wang Yunfeng Diao Zichang Tan G. Guo AAML 48 10 0 09 Mar 2022
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 29 69 0 21 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min-Bin Lin Xiao Yang Junyi Zhu Shuicheng Yan 30 119 0 21 Feb 2022
Energy-Based Contrastive Learning of Visual Representations Beomsu Kim Jong Chul Ye 13 16 0 10 Feb 2022
Modeling Structure with Undirected Neural Networks Tsvetomila Mihaylova Vlad Niculae André F. T. Martins GNN 15 1 0 08 Feb 2022
Learning Representation from Neural Fisher Kernel with Low-rank Approximation Ruixiang Zhang Shuangfei Zhai Etai Littwin J. Susskind SSL 28 3 0 04 Feb 2022
Energy-bounded Learning for Robust Models of Code Nghi D. Q. Bui Yijun Yu OODD 35 2 0 20 Dec 2021
Active Learning for Domain Adaptation: An Energy-Based Approach Binhui Xie Longhui Yuan Shuang Li Chi Harold Liu Xinjing Cheng Guoren Wang 21 107 0 02 Dec 2021
Particle Dynamics for Learning EBMs Kirill Neklyudov P. Jaini Max Welling DiffM 34 0 0 26 Nov 2021
Consensus Synergizes with Memory: A Simple Approach for Anomaly Segmentation in Urban Scenes Jiazhong Cen Zekun Jiang Lingxi Xie Qi Tian Dongsheng Jiang Wei Shen 32 5 0 24 Nov 2021
Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes Yu Tian Yuyuan Liu Guansong Pang Fengbei Liu Yuanhong Chen G. Carneiro 23 84 0 24 Nov 2021
Learning to Compose Visual Relations Nan Liu Shuang Li Yilun Du J. Tenenbaum Antonio Torralba CoGe OCL 29 77 0 17 Nov 2021
Unsupervised Learning of Compositional Energy Concepts Yilun Du Shuang Li Yash Sharma J. Tenenbaum Igor Mordatch CoGe OCL 21 76 0 04 Nov 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Greg Ver Steeg Aram Galstyan 33 13 0 03 Nov 2021
A Unified View of cGANs with and without Classifiers Si-An Chen Chun-Liang Li Hsuan-Tien Lin GAN 20 10 0 01 Nov 2021
Pseudo-Spherical Contrastive Divergence Lantao Yu Jiaming Song Yang Song Stefano Ermon 23 7 0 01 Nov 2021
Learning Deep Representation with Energy-Based Self-Expressiveness for Subspace Clustering Yanming Li Changsheng Li Shiye Wang Ye Yuan Guoren Wang SSL 31 0 0 28 Oct 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 41 80 0 26 Oct 2021
Learning Proposals for Practical Energy-Based Regression L. Kumar Martin Danelljan Thomas B. Schon 30 4 0 22 Oct 2021
Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation Bingbin Liu Elan Rosenfeld Pradeep Ravikumar Andrej Risteski 23 13 0 21 Oct 2021
Controllable and Compositional Generation with Latent-Space Energy-Based Models Weili Nie Arash Vahdat Anima Anandkumar 22 78 0 21 Oct 2021
Adversarial Purification through Representation Disentanglement Tao Bai Jun Zhao Lanqing Guo B. Wen AAML 17 1 0 15 Oct 2021
Well-classified Examples are Underestimated in Classification with Deep Neural Networks Guangxiang Zhao Wenkai Yang Xuancheng Ren Lei Li Yunfang Wu Xu Sun 25 15 0 13 Oct 2021
Meta Learning Low Rank Covariance Factors for Energy-Based Deterministic Uncertainty Jeffrey Willette Haebeom Lee Juho Lee Sung Ju Hwang OODD OOD 36 1 0 12 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation Dennis Ulmer Christian Hardmeier J. Frellsen BDL UQCV UD EDL PER 45 48 0 06 Oct 2021
Score-Based Generative Classifiers Roland S. Zimmermann Lukas Schott Yang Song Benjamin A. Dunn David A. Klindt DiffM 22 64 0 01 Oct 2021
JEM++: Improved Techniques for Training JEM Xiulong Yang Shihao Ji AAML VLM 18 27 0 19 Sep 2021
The Functional Correspondence Problem Zihang Lai Senthil Purushwalkam Abhinav Gupta 38 13 0 02 Sep 2021
Implicit Behavioral Cloning Peter R. Florence Corey Lynch Andy Zeng Oscar Ramirez Ayzaan Wahid Laura Downs Adrian S. Wong Johnny Lee Igor Mordatch Jonathan Tompson OffRL 49 368 0 01 Sep 2021
Learning Energy-Based Approximate Inference Networks for Structured Applications in NLP Lifu Tu BDL 35 0 0 27 Aug 2021
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework Ammar Mansoor Kamoona A. Gostar A. Bab-Hadiashar R. Hoseinnezhad 17 16 0 27 Aug 2021
Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification Bo Pang Ying Nian Wu 24 18 0 26 Aug 2021
Revealing the Distributional Vulnerability of Discriminators by Implicit Generators Zhilin Zhao LongBing Cao Kun-Yu Lin 29 11 0 23 Aug 2021
Towards Understanding the Generative Capability of Adversarially Robust Classifiers Yao Zhu Jiacheng Ma Jiacheng Sun Zewei Chen Rongxin Jiang Zhenguo Li AAML 18 21 0 20 Aug 2021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration Yezhen Wang Bo-wen Li Tong Che Kaiyang Zhou Ziwei Liu Dongsheng Li UQCV 22 47 0 27 Jul 2021
Energy-based Unknown Intent Detection with Data Manipulation Yawen Ouyang Jiasheng Ye Yu Chen Xinyu Dai Shujian Huang Jiajun Chen 17 21 0 27 Jul 2021
Directly Training Joint Energy-Based Models for Conditional Synthesis and Calibrated Prediction of Multi-Attribute Data Jacob Kelly R. Zemel Will Grathwohl 36 2 0 19 Jul 2021
On the Importance of Regularisation & Auxiliary Information in OOD Detection John Mitros Brian Mac Namee 21 2 0 15 Jul 2021