How to Train Your Energy-Based Models

9 January 2021

Papers citing "How to Train Your Energy-Based Models"

50 / 150 papers shown

Title
Stabilized training of joint energy-based models and their practical applications Martin Sustek Samik Sadhu L. Burget H. Hermansky Jesus Villalba Laureano Moro Velázquez Najim Dehak AAML VLM 13 1 0 07 Mar 2023
Diffusion Model-Augmented Behavioral Cloning Shangcheng Chen Hsiang-Chun Wang Ming-Hao Hsu Chun-Mao Lai Shao-Hua Sun DiffM 47 31 0 26 Feb 2023
Energy-Based Test Sample Adaptation for Domain Generalization Zehao Xiao Xiantong Zhen Shengcai Liao Cees G. M. Snoek TTA 48 17 0 22 Feb 2023
A Text-guided Protein Design Framework Shengchao Liu Yanjing Li Zhuoxinran Li A. Gitter Yutao Zhu ... Arvind Ramanathan Chaowei Xiao Jian Tang Hongyu Guo Anima Anandkumar 65 61 0 09 Feb 2023
Mind the Gap: Offline Policy Optimization for Imperfect Rewards Jianxiong Li Xiao Hu Haoran Xu Jingjing Liu Xianyuan Zhan Qing-Shan Jia Ya-Qin Zhang OffRL 38 19 0 03 Feb 2023
MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows Mingxuan Yi Zhanxing Zhu Song Liu GAN 24 13 0 02 Feb 2023
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics Marloes Arts Victor Garcia Satorras Chin-Wei Huang Daniel Zuegner Marco Federici C. Clementi Frank Noé Robert Pinsler Rianne van den Berg DiffM 11 85 0 01 Feb 2023
A survey and taxonomy of loss functions in machine learning Lorenzo Ciampiconi A. Elwood Marco Leonardi A. Mohamed A. Rozza MU FaML 9 25 0 13 Jan 2023
Detecting Objects with Context-Likelihood Graphs and Graph Refinement Aritra Bhowmik Yu Wang N. Baka Martin R. Oswald Cees G. M. Snoek 19 2 0 23 Dec 2022
Robust Graph Representation Learning via Predictive Coding Billy Byiringiro Tommaso Salvatori Thomas Lukasiewicz OOD 25 6 0 09 Dec 2022
End-to-End Stochastic Optimization with Energy-Based Model Lingkai Kong Jiaming Cui Yuchen Zhuang Rui Feng B. Prakash Chao Zhang 13 16 0 25 Nov 2022
Self-Adapting Noise-Contrastive Estimation for Energy-Based Models Na Xu 4 2 0 03 Nov 2022
Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions C. Ekbote Moksh Jain Payel Das Yoshua Bengio 40 4 0 01 Nov 2022
Minimum Kernel Discrepancy Estimators Chris J. Oates 24 10 0 28 Oct 2022
Improving abstractive summarization with energy-based re-ranking Diogo Pernes Afonso Mendes André F. T. Martins 23 6 0 27 Oct 2022
Maximum Likelihood Learning of Unnormalized Models for Simulation-Based Inference Pierre Glaser Michael Arbel Samo Hromadka Arnaud Doucet A. Gretton 25 2 0 26 Oct 2022
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models Meng Liu Haoran Liu Shuiwang Ji 24 5 0 11 Oct 2022
Hiding Images in Deep Probabilistic Models Haoyu Chen Linqi Song Zhenxing Qian Xinpeng Zhang Kede Ma AAML 11 10 0 05 Oct 2022
Denoising MCMC for Accelerating Diffusion-Based Generative Models Beomsu Kim Jong Chul Ye DiffM 49 13 0 29 Sep 2022
Towards Healing the Blindness of Score Matching Mingtian Zhang Oscar Key Peter Hayes David Barber Brooks Paige F. Briol MedIm 55 14 0 15 Sep 2022
SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion Julen Urain Niklas Funk Jan Peters Georgia Chalvatzaki DiffM 55 118 0 08 Sep 2022
A Survey on Generative Diffusion Model Hanqun Cao Cheng Tan Zhangyang Gao Yilun Xu Guangyong Chen Pheng-Ann Heng Stan Z. Li MedIm 37 206 0 06 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications Ling Yang Zhilong Zhang Yingxia Shao Shenda Hong Runsheng Xu Yue Zhao Wentao Zhang Bin Cui Ming-Hsuan Yang DiffM MedIm 224 1,302 0 02 Sep 2022
Understanding Diffusion Models: A Unified Perspective Calvin Luo DiffM 13 332 0 25 Aug 2022
Semantic Driven Energy based Out-of-Distribution Detection Abhishek Joshi Sathish Chalasani K. N. Iyer OODD 26 4 0 23 Aug 2022
RenyiCL: Contrastive Representation Learning with Skew Renyi Divergence Kyungmin Lee Jinwoo Shin SSL DRL 29 10 0 12 Aug 2022
Implicit Two-Tower Policies Yunfan Zhao Qingkai Pan K. Choromanski Deepali Jain Vikas Sindhwani OffRL 28 3 0 02 Aug 2022
Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models Ozan Özdenizci R. Legenstein DiffM 30 240 0 29 Jul 2022
Comparing the latent space of generative models Andrea Asperti Valerio Tonelli DRL 21 12 0 14 Jul 2022
Statistical applications of contrastive learning Michael U. Gutmann Steven Kleinegesse Benjamin Rhodes 18 7 0 29 Apr 2022
Learning Implicit Priors for Motion Optimization Julen Urain An T. Le Alexander Lambert Georgia Chalvatzaki Byron Boots Jan Peters 28 24 0 11 Apr 2022
Learning to Solve Travelling Salesman Problem with Hardness-adaptive Curriculum Zeyang Zhang Ziwei Zhang Xin Eric Wang Wenwu Zhu 17 42 0 07 Apr 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design Yuanqi Du Tianfan Fu Jimeng Sun Shengchao Liu AI4CE 28 86 0 28 Mar 2022
Structured Multi-task Learning for Molecular Property Prediction Shengchao Liu Meng Qu Zuobai Zhang Huiyu Cai Jian Tang 13 24 0 22 Feb 2022
Solving Inverse Problems in Medical Imaging with Score-Based Generative Models Yang Song Liyue Shen Lei Xing Stefano Ermon DiffM SyDa OffRL MedIm 30 511 0 15 Nov 2021
Estimating High Order Gradients of the Data Distribution by Denoising Chenlin Meng Yang Song Wenzhe Li Stefano Ermon DiffM 8 45 0 08 Nov 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Greg Ver Steeg Aram Galstyan 33 13 0 03 Nov 2021
Controllable and Compositional Generation with Latent-Space Energy-Based Models Weili Nie Arash Vahdat Anima Anandkumar 17 78 0 21 Oct 2021
Score-based diffusion models for accelerated MRI Hyungjin Chung Jong Chul Ye DiffM MedIm 39 399 0 08 Oct 2021
Pre-training Molecular Graph Representation with 3D Geometry Shengchao Liu Hanchen Wang Weiyang Liu Joan Lasenby Hongyu Guo Jian Tang 117 302 0 07 Oct 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 49 369 0 01 Sep 2021
Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks Carles Domingo-Enrich A. Bietti Marylou Gabrié Joan Bruna Eric Vanden-Eijnden FedML 32 6 0 11 Jul 2021
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification Alkis Gotovos R. Burkholz John Quackenbush Stefanie Jegelka 16 8 0 06 Jul 2021
ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models Tijin Yan Hongwei Zhang Tong Zhou Yufeng Zhan Yuanqing Xia DiffM AI4TS 30 38 0 18 Jun 2021
Learning to Efficiently Sample from Diffusion Probabilistic Models Daniel Watson Jonathan Ho Mohammad Norouzi William Chan DiffM 39 134 0 07 Jun 2021
A Variational Perspective on Diffusion-Based Generative Models and Score Matching Chin-Wei Huang Jae Hyun Lim Aaron Courville DiffM 35 186 0 05 Jun 2021
Autoencoding Under Normalization Constraints Sangwoong Yoon Yung-Kyun Noh Frank C. Park OODD UQCV 27 38 0 12 May 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 36 478 0 08 Mar 2021
Training Deep Energy-Based Models with f-Divergence Minimization Lantao Yu Yang Song Jiaming Song Stefano Ermon 176 42 0 06 Mar 2020
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 233 2,545 0 25 Jan 2016