Deep Directed Generative Models with Energy-Based Probability Estimation

10 June 2016

Papers citing "Deep Directed Generative Models with Energy-Based Probability Estimation"

50 / 59 papers shown

Title
Exploring bidirectional bounds for minimax-training of Energy-based models Cong Geng Jia Wang Li Chen Zhiyong Gao J. Frellsen Søren Hauberg 95 0 0 05 Jun 2025
Energy-based Preference Optimization for Test-time Adaptation Yewon Han Seoyun Yang Taesup Kim TTA 286 0 0 26 May 2025
Time-series Generation by Contrastive Imitation Daniel Jarrett Ioana Bica M. Schaar AI4TS 82 24 0 02 Nov 2023
Progressive Energy-Based Cooperative Learning for Multi-Domain Image-to-Image Translation Weinan Song Y. Zhu Lei He Yingnian Wu Jianwen Xie 71 1 0 26 Jun 2023
Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting Deqian Kong Bo Pang Tian Han Ying Nian Wu DiffM 77 7 0 09 Jun 2023
Persistently Trained, Diffusion-assisted Energy-based Models Xinwei Zhang Z. Tan Zhijian Ou DiffM 75 2 0 21 Apr 2023
Explaining the effects of non-convergent sampling in the training of Energy-Based Models E. Agoritsas Giovanni Catania A. Decelle Beatriz Seoane DiffM 68 10 0 23 Jan 2023
Learning Probabilistic Models from Generator Latent Spaces with Hat EBM Mitch Hill Erik Nijkamp Jonathan Mitchell Bo Pang Song-Chun Zhu 405 12 0 29 Oct 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications Ling Yang Zhilong Zhang Yingxia Shao Shenda Hong Runsheng Xu Yue Zhao Wentao Zhang Tengjiao Wang Ming-Hsuan Yang DiffM MedIm 485 1,420 0 02 Sep 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 31 0 0 24 May 2022
Learning to Compose Visual Relations Nan Liu Shuang Li Yilun Du J. Tenenbaum Antonio Torralba CoGe OCL 91 80 0 17 Nov 2021
Unsupervised Learning of Compositional Energy Concepts Yilun Du Shuang Li Yash Sharma J. Tenenbaum Igor Mordatch CoGe OCL 93 81 0 04 Nov 2021
Bounds all around: training energy-based models with bidirectional bounds Cong Geng Jia Wang Zhiyong Gao J. Frellsen Søren Hauberg 77 16 0 01 Nov 2021
LEO: Learning Energy-based Models in Factor Graph Optimization Paloma Sodhi Eric Dexheimer Mustafa Mukadam Stuart Anderson Michael Kaess 98 17 0 04 Aug 2021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration Yezhen Wang Yue Liu Tong Che Kaiyang Zhou Ziwei Liu Dongsheng Li UQCV 93 51 0 27 Jul 2021
Deep Consensus Learning Wei Sun Tianfu Wu 68 2 0 15 Mar 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 176 508 0 08 Mar 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 102 265 0 09 Jan 2021
A Distributional Approach to Controlled Text Generation Muhammad Khalifa Hady ElSahar Marc Dymetman 167 119 0 21 Dec 2020
Learning Energy-Based Models by Diffusion Recovery Likelihood Ruiqi Gao Yang Song Ben Poole Ying Nian Wu Diederik P. Kingma DiffM 97 128 0 15 Dec 2020
Improved Contrastive Divergence Training of Energy Based Models Yilun Du Shuang Li J. Tenenbaum Igor Mordatch 141 144 0 02 Dec 2020
Improving GAN Training with Probability Ratio Clipping and Sample Reweighting Yue Wu Pan Zhou A. Wilson Eric Xing Zhiting Hu GAN 110 36 0 12 Jun 2020
Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization G. Rizzuti Ali Siahkoohi Philipp A. Witte Felix J. Herrmann UQCV 83 20 0 16 Apr 2020
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator Yuxuan Song Qiwei Ye Minkai Xu Tie-Yan Liu 65 8 0 05 Apr 2020
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling Tong Che Ruixiang Zhang Jascha Narain Sohl-Dickstein Hugo Larochelle Liam Paull Yuan Cao Yoshua Bengio DiffM DRL 85 114 0 12 Mar 2020
Learning Generative Models using Denoising Density Estimators Siavash Bigdeli Geng Lin Tiziano Portenier L. A. Dunbar Matthias Zwicker DiffM 104 16 0 08 Jan 2020
Distributional Reinforcement Learning for Energy-Based Sequential Models Tetiana Parshakova J. Andreoli Marc Dymetman 83 21 0 18 Dec 2019
Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference Erik Nijkamp Bo Pang Tian Han Linqi Zhou Song-Chun Zhu Ying Nian Wu BDL DRL 87 2 0 04 Dec 2019
Flow Contrastive Estimation of Energy-Based Models Ruiqi Gao Erik Nijkamp Diederik P. Kingma Zhen Xu Andrew M. Dai Ying Nian Wu GAN 101 115 0 02 Dec 2019
Adversarial Fisher Vectors for Unsupervised Representation Learning Shuangfei Zhai Walter A. Talbott Carlos Guestrin J. Susskind GAN 105 9 0 29 Oct 2019
Model Based Planning with Energy Based Models Yilun Du Toru Lin Igor Mordatch 97 38 0 15 Sep 2019
$$(1 + \varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets$ $(1 + \varepsilon)$ -class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets M. Borisyak Artem Sergeevich Ryzhikov Andrey Ustyuzhanin D. Derkach Fedor Ratnikov Olga Mineeva 32 4 0 14 Jun 2019
Exponential Family Estimation via Adversarial Dynamics Embedding Bo Dai Ziqiang Liu H. Dai Niao He Arthur Gretton Le Song Dale Schuurmans 82 53 0 27 Apr 2019
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model Erik Nijkamp Mitch Hill Song-Chun Zhu Ying Nian Wu 124 214 0 22 Apr 2019
Learning Probabilistic Multi-Modal Actor Models for Vision-Based Robotic Grasping Mengyuan Yan A. Li Mrinal Kalakrishnan P. Pastor 57 18 0 15 Apr 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 109 156 0 29 Mar 2019
Maximum Entropy Generators for Energy-Based Models Rithesh Kumar Sherjil Ozair Anirudh Goyal Aaron Courville Yoshua Bengio 58 113 0 24 Jan 2019
Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model Tian Han Erik Nijkamp Xiaolin Fang Mitch Hill Song-Chun Zhu Ying Nian Wu 87 68 0 28 Dec 2018
Concept Learning with Energy-Based Models William J. Wilkinson 161 26 0 06 Nov 2018
A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models Ying Nian Wu Ruiqi Gao Tian Han Song-Chun Zhu TPM 57 18 0 09 Oct 2018
A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling Zhijian Ou 100 16 0 05 Aug 2018
Deep PDF: Probabilistic Surface Optimization and Density Estimation Dmitry Kopitkov Vadim Indelman 36 2 0 27 Jul 2018
Parametric generation of conditional geological realizations using generative neural networks Shing Chan A. Elsheikh OOD GAN AI4CE 145 101 0 13 Jul 2018
Deep Generative Models with Learnable Knowledge Constraints Zhiting Hu Zichao Yang Ruslan Salakhutdinov Xiaodan Liang Lianhui Qin Haoye Dong Eric Xing BDL AI4CE 107 76 0 26 Jun 2018
Generative Modeling by Inclusive Neural Random Fields with Applications in Image Generation and Anomaly Detection Yunfu Song Zhijian Ou DiffM 107 30 0 01 Jun 2018
Learning Energy-Based Models as Generative ConvNets via Multi-grid Modeling and Sampling Ruiqi Gao Yang Lu Junpei Zhou Song-Chun Zhu Ying Nian Wu 112 79 0 26 Sep 2017
Inception Score, Label Smoothing, Gradient Vanishing and -log(D(x)) Alternative Zhiming Zhou Weinan Zhang Jun Wang 83 19 0 05 Aug 2017
MMGAN: Manifold Matching Generative Adversarial Network Noseong Park A. Anand Joel Ruben Antony Moniz Kookjin Lee Tanmoy Chakraborty Jaegul Choo Hongkyu Park Youngmin Kim GAN 117 8 0 26 Jul 2017
Learning Deep Energy Models: Contrastive Divergence vs. Amortized MLE Qiang Liu Dilin Wang 78 23 0 04 Jul 2017
Reinforcement Learning with Deep Energy-Based Policies Tuomas Haarnoja Haoran Tang Pieter Abbeel Sergey Levine 124 1,350 0 27 Feb 2017