Generative Modeling by Estimating Gradients of the Data Distribution

12 July 2019

Papers citing "Generative Modeling by Estimating Gradients of the Data Distribution"

22 / 2,622 papers shown

Title
Solving Inverse Problems with a Flow-based Noise Model Jay Whang Qi Lei A. Dimakis 68 36 0 18 Mar 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 27 113 0 12 Mar 2020
Permutation Invariant Graph Generation via Score-Based Generative Modeling Chenhao Niu Yang Song Jiaming Song Shengjia Zhao Aditya Grover Stefano Ermon DiffM 34 265 0 02 Mar 2020
Composing Normalizing Flows for Inverse Problems Jay Whang Erik M. Lindgren A. Dimakis TPM 53 50 0 26 Feb 2020
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA Ilyes Khemakhem R. Monti Diederik P. Kingma Aapo Hyvarinen CML 22 112 0 26 Feb 2020
Bidirectional Generative Modeling Using Adversarial Gradient Estimation Xinwei Shen Tong Zhang Kani Chen GAN 30 9 0 21 Feb 2020
Source Separation with Deep Generative Priors V. Jayaram John Thickstun 26 38 0 19 Feb 2020
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud R. Zemel 22 14 0 13 Feb 2020
Fast Convergence for Langevin Diffusion with Manifold Structure Ankur Moitra Andrej Risteski 27 7 0 13 Feb 2020
Generative Modeling with Denoising Auto-Encoders and Langevin Sampling Adam Block Youssef Mroueh Alexander Rakhlin DiffM 31 99 0 31 Jan 2020
Learning Generative Models using Denoising Density Estimators Siavash Bigdeli Geng Lin Tiziano Portenier L. A. Dunbar Matthias Zwicker DiffM 52 16 0 08 Jan 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 48 534 0 06 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 31 113 0 02 Dec 2019
A Near-Optimal Gradient Flow for Learning Neural Energy-Based Models Yang Wu Pengxu Wei Liang Lin 35 0 0 31 Oct 2019
Bridging the Gap Between $f$ -GANs and Wasserstein GANs Jiaming Song Stefano Ermon 30 40 0 22 Oct 2019
Learning Energy-Based Models in High-Dimensional Spaces with Multi-scale Denoising Score Matching Zengyi Li Yubei Chen Friedrich T. Sommer DiffM 13 27 0 17 Oct 2019
Injecting Hierarchy with U-Net Transformers David Donahue Vladislav Lialin Anna Rumshisky AI4CE 24 1 0 16 Oct 2019
Demon: Improved Neural Network Training with Momentum Decay John Chen Cameron R. Wolfe Zhaoqi Li Anastasios Kyrillidis ODL 29 15 0 11 Oct 2019
Oblique Decision Trees from Derivatives of ReLU Networks Guang-He Lee Tommi Jaakkola 38 23 0 30 Sep 2019
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 397 10,443 0 12 Dec 2018
A Learned Representation For Artistic Style Vincent Dumoulin Jonathon Shlens M. Kudlur GAN 233 1,160 0 24 Oct 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 291 2,559 0 25 Jan 2016