Generative Modeling by Estimating Gradients of the Data Distribution

12 July 2019

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

50 / 2,622 papers shown

Title
SNIPS: Solving Noisy Inverse Problems Stochastically Bahjat Kawar Gregory Vaksman Michael Elad 50 190 0 31 May 2021
Cascaded Diffusion Models for High Fidelity Image Generation Jonathan Ho Chitwan Saharia William Chan David J. Fleet Mohammad Norouzi Tim Salimans 95 1,191 0 30 May 2021
Diffusion-Based Representation Learning K. Abstreiter Sarthak Mittal Stefan Bauer Bernhard Schölkopf Arash Mehrjou DiffM 35 57 0 29 May 2021
Gotta Go Fast When Generating Data with Score-Based Models Alexia Jolicoeur-Martineau Ke Li Remi Piche-Taillefer Tal Kachman Ioannis Mitliagkas DiffM 39 217 0 28 May 2021
DiffSVC: A Diffusion Probabilistic Model for Singing Voice Conversion Songxiang Liu Yuewen Cao Dan Su Helen Meng DiffM 32 58 0 28 May 2021
Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics V. Jayaram John Thickstun DiffM 33 24 0 17 May 2021
Unsupervised Deep Learning Methods for Biological Image Reconstruction and Enhancement Mehmet Akccakaya Burhaneddin Yaman Hyungjin Chung Jong Chul Ye MedIm 64 55 0 17 May 2021
ItôTTS and ItôWave: Linear Stochastic Differential Equation Is All You Need For Audio Generation Shoule Wu Ziqiang Shi DiffM 52 11 0 17 May 2021
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech Vadim Popov Ivan Vovk Vladimir Gogoryan Tasnima Sadekova Mikhail Kudinov DiffM 66 518 0 13 May 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 90 7,577 0 11 May 2021
EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models Jiaxiang Wu Shitong Luo Tao Shen Haidong Lan Sheng Wang Junzhou Huang DiffM 30 8 0 11 May 2021
Learning High-Dimensional Distributions with Latent Neural Fokker-Planck Kernels Yufan Zhou Changyou Chen Jinhui Xu 22 2 0 10 May 2021
A likelihood approach to nonparametric estimation of a singular distribution using deep generative models Minwoo Chae Dongha Kim Yongdai Kim Lizhen Lin 56 17 0 09 May 2021
Learning Gradient Fields for Molecular Conformation Generation Chence Shi Shitong Luo Minkai Xu Jian Tang DiffM AI4CE 42 214 0 09 May 2021
DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism Jinglin Liu Chengxi Li Yi Ren Feiyang Chen Zhou Zhao DiffM 58 260 0 06 May 2021
VideoGPT: Video Generation using VQ-VAE and Transformers Wilson Yan Yunzhi Zhang Pieter Abbeel A. Srinivas ViT VGen 250 491 0 20 Apr 2021
On Energy-Based Models with Overparametrized Shallow Neural Networks Carles Domingo-Enrich A. Bietti Eric Vanden-Eijnden Joan Bruna BDL 47 9 0 15 Apr 2021
UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models Hiroshi Sasaki Chris G. Willcocks T. Breckon DiffM 23 162 0 12 Apr 2021
On tuning consistent annealed sampling for denoising score matching Joan Serrà Santiago Pascual Jordi Pons DiffM 30 6 0 08 Apr 2021
Creativity and Machine Learning: A Survey Giorgio Franceschelli Mirco Musolesi VLM AI4CE 39 40 0 06 Apr 2021
Noise Estimation for Generative Diffusion Models Robin San-Roman Eliya Nachmani Lior Wolf DiffM 44 105 0 06 Apr 2021
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling Junhyeok Lee Seungu Han DiffM 29 67 0 06 Apr 2021
Symbolic Music Generation with Diffusion Models Gautam Mittal Jesse Engel Curtis Hawthorne Ian Simon MGen DiffM 57 190 0 30 Mar 2021
Improved Autoregressive Modeling with Distribution Smoothing Chenlin Meng Jiaming Song Yang Song Shengjia Zhao Stefano Ermon DiffM 32 23 0 28 Mar 2021
Synthesize-It-Classifier: Learning a Generative Classifier through RecurrentSelf-analysis Arghya Pal Raphaël C.-W. Phan Koksheik Wong DiffM 36 3 0 26 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 51 491 0 08 Mar 2021
Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie R. Laumont Valentin De Bortoli Andrés Almansa J. Delon Alain Durmus Marcelo Pereyra 36 109 0 08 Mar 2021
Energy-Based Learning for Scene Graph Generation M. Suhail Abhay Mittal Behjat Siddiquie Chris Broaddus J. Eledath Gérard Medioni Leonid Sigal 53 160 0 03 Mar 2021
Provable Compressed Sensing with Generative Priors via Langevin Dynamics Thanh V. Nguyen Gauri Jagatap Chinmay Hegde GAN 43 13 0 25 Feb 2021
EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss Zhisheng Xiao Qing Yan Y. Amit 37 2 0 23 Feb 2021
Anytime Sampling for Autoregressive Models via Ordered Autoencoding Yilun Xu Yang Song Sahaj Garg Linyuan Gong Rui Shu Aditya Grover Stefano Ermon DiffM 48 11 0 23 Feb 2021
Improved Denoising Diffusion Probabilistic Models Alex Nichol Prafulla Dhariwal DiffM 65 3,582 0 18 Feb 2021
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions Will Grathwohl Kevin Swersky Milad Hashemi David Duvenaud Chris J. Maddison BDL 30 94 0 08 Feb 2021
Neural SDEs as Infinite-Dimensional GANs Patrick Kidger James Foster Xuechen Li Harald Oberhauser Terry Lyons DiffM 16 146 0 06 Feb 2021
Active Slices for Sliced Stein Discrepancy Wenbo Gong Kaibo Zhang Yingzhen Li José Miguel Hernández-Lobato 38 8 0 05 Feb 2021
GraphEBM: Molecular Graph Generation with Energy-Based Models Meng Liu Keqiang Yan Bora Oztekin Shuiwang Ji 24 88 0 31 Jan 2021
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting Kashif Rasul Calvin Seward Ingmar Schuster Roland Vollgraf DiffM 47 309 0 28 Jan 2021
Adversarial Text-to-Image Synthesis: A Review Stanislav Frolov Tobias Hinz Federico Raue Jörn Hees Andreas Dengel EGVM 32 176 0 25 Jan 2021
Stochastic Image Denoising by Sampling from the Posterior Distribution Bahjat Kawar Gregory Vaksman Michael Elad DiffM 35 62 0 23 Jan 2021
Maximum Likelihood Training of Score-Based Diffusion Models Yang Song Conor Durkan Iain Murray Stefano Ermon DiffM 69 635 0 22 Jan 2021
DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training Jiaheng Wei Minghao Liu Jiahao Luo Andrew Zhu James Davis Yang Liu GAN 74 11 0 19 Jan 2021
Denoising Score Matching with Random Fourier Features Olga Tsymboi Yermek Kapushev Evgeny Burnaev Ivan Oseledets 44 1 0 13 Jan 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 38 249 0 09 Jan 2021
Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed Eric Luhman Troy Luhman DiffM 197 263 0 07 Jan 2021
Joint Intensity-Gradient Guided Generative Modeling for Colorization Kai Hong Jin Li Wanyun Li Cailian Yang Minghui Zhang Yuhao Wang Qiegen Liu GAN 28 0 0 28 Dec 2020
Image Synthesis with Adversarial Networks: a Comprehensive Survey and Case Studies Pourya Shamsolmoali Masoumeh Zareapoor Eric Granger Huiyu Zhou Ruili Wang M. E. Celebi Jie Yang EGVM 59 140 0 26 Dec 2020
Learning Energy-Based Models by Diffusion Recovery Likelihood Ruiqi Gao Yang Song Ben Poole Ying Nian Wu Diederik P. Kingma DiffM 34 124 0 15 Dec 2020
Learning Energy-Based Models With Adversarial Training Xuwang Yin Shiying Li Gustavo K. Rohde AAML DiffM 64 9 0 11 Dec 2020
Generative Learning With Euler Particle Transport Yuan Gao Jian Huang Yuling Jiao Jin Liu Xiliang Lu J. Yang OT 33 2 0 11 Dec 2020
Contrastive Divergence Learning is a Time Reversal Adversarial Game Omer Yair T. Michaeli GAN 26 6 0 06 Dec 2020