Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models

8 March 2021

Papers citing "Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models"

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Title
Diffusion Probabilistic Generative Models for Accelerated, in-NICU Permanent Magnet Neonatal MRI Yamin Arefeen Brett Levac Bhairav Patel Chang Ho Jonathan I. Tamir DiffM MedIm 31 0 0 21 May 2025
Overcoming Dimensional Factorization Limits in Discrete Diffusion Models through Quantum Joint Distribution Learning Chuangtao Chen Qinglin Zhao Mengchu Zhou Zhimin He Haozhen Situ DiffM 129 0 0 08 May 2025
Surrogate modeling of Cellular-Potts Agent-Based Models as a segmentation task using the U-Net neural network architecture Tien Comlekoglu J. Q. Toledo-Marín Tina Comlekoglu Douglas W. DeSimone Shayn M. Peirce Geoffrey C. Fox J. Glazier 99 1 0 01 May 2025
Deep Generative Model-Based Generation of Synthetic Individual-Specific Brain MRI Segmentations Ruijie Wang Luca Rossetto Susan Mérillat Christina Röcke Mike Martin Abraham Bernstein DiffM MedIm 115 0 0 15 Apr 2025
Double Blind Imaging with Generative Modeling Brett Levac A. Jalal Kannan Ramchandran Jonathan I. Tamir DiffM MedIm 106 0 0 27 Mar 2025
Beyond Batch Learning: Global Awareness Enhanced Domain Adaptation Lingkun Luo Shiqiang Hu Liming Chen 111 0 0 10 Feb 2025
EDSep: An Effective Diffusion-Based Method for Speech Source Separation Jinwei Dong Xinsheng Wang Qirong Mao 96 1 0 28 Jan 2025
Synthesizing Forestry Images Conditioned on Plant Phenotype Using a Generative Adversarial Network Debasmita Pal Arun Ross GAN 110 1 0 17 Jan 2025
Expert-elicitation method for non-parametric joint priors using normalizing flows F. Bockting Stefan T. Radev Paul-Christian Bürkner BDL 135 1 0 24 Nov 2024
A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization Aron Brenner Rahman Khorramfar Jennifer Sun Saurabh Amin 107 0 0 05 Sep 2024
A Pattern Language for Machine Learning Tasks Benjamin Rodatz Ian Fan Tuomas Laakkonen Neil John Ortega Thomas Hoffman Vincent Wang-Ma'scianica 71 3 0 02 Jul 2024
Discrete Distribution Networks Lei Yang 59 1 0 29 Dec 2023
Conditional Generative Modeling for High-dimensional Marked Temporal Point Processes Zheng Dong Zekai Fan Shixiang Zhu DiffM 53 4 0 21 May 2023
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 138 30,021 0 01 Mar 2022
Alias-Free Generative Adversarial Networks Tero Karras M. Aittala S. Laine Erik Härkönen Janne Hellsten J. Lehtinen Timo Aila GAN 148 1,582 0 23 Jun 2021
Score-based Generative Modeling in Latent Space Arash Vahdat Karsten Kreis Jan Kautz DiffM 32 667 0 10 Jun 2021
Learning to Efficiently Sample from Diffusion Probabilistic Models Daniel Watson Jonathan Ho Mohammad Norouzi William Chan DiffM 64 135 0 07 Jun 2021
Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings Kartik Goyal Chris Dyer Taylor Berg-Kirkpatrick 112 51 0 04 Jun 2021
Gotta Go Fast When Generating Data with Score-Based Models Alexia Jolicoeur-Martineau Ke Li Remi Piche-Taillefer Tal Kachman Ioannis Mitliagkas DiffM 55 218 0 28 May 2021
UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models Hiroshi Sasaki Chris G. Willcocks T. Breckon DiffM 43 163 0 12 Apr 2021
Improved Autoregressive Modeling with Distribution Smoothing Chenlin Meng Jiaming Song Yang Song Shengjia Zhao Stefano Ermon DiffM 37 23 0 28 Mar 2021
Generative Minimization Networks: Training GANs Without Competition Paulina Grnarova Yannic Kilcher Kfir Y. Levy Aurelien Lucchi Thomas Hofmann GAN 26 6 0 23 Mar 2021
Implicit Normalizing Flows Cheng Lu Jianfei Chen Chongxuan Li Qiuhao Wang Jun Zhu AI4CE 39 34 0 17 Mar 2021
Anycost GANs for Interactive Image Synthesis and Editing Ji Lin Richard Y. Zhang F. Ganz Song Han Jun-Yan Zhu 70 85 0 04 Mar 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 319 4,873 0 24 Feb 2021
Improved Denoising Diffusion Probabilistic Models Alex Nichol Prafulla Dhariwal DiffM 173 3,599 0 18 Feb 2021
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom Didrik Nielsen P. Jaini Patrick Forré Max Welling DiffM 263 414 0 10 Feb 2021
Generative Models as Distributions of Functions Emilien Dupont Yee Whye Teh Arnaud Doucet 39 103 0 09 Feb 2021
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions Will Grathwohl Kevin Swersky Milad Hashemi David Duvenaud Chris J. Maddison BDL 43 96 0 08 Feb 2021
Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis Bingchen Liu Yizhe Zhu Kunpeng Song Ahmed Elgammal 203 238 0 12 Jan 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 47 252 0 09 Jan 2021
Taming Transformers for High-Resolution Image Synthesis Patrick Esser Robin Rombach Bjorn Ommer ViT 93 2,890 0 17 Dec 2020
Learning Energy-Based Models by Diffusion Recovery Likelihood Ruiqi Gao Yang Song Ben Poole Ying Nian Wu Diederik P. Kingma DiffM 49 126 0 15 Dec 2020
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 262 6,293 0 26 Nov 2020
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images R. Child BDL VLM 158 343 0 20 Nov 2020
Autoregressive Score Matching Chenlin Meng Lantao Yu Yang Song Jiaming Song Stefano Ermon DiffM 218 13 0 24 Oct 2020
No MCMC for me: Amortized sampling for fast and stable training of energy-based models Will Grathwohl Jacob Kelly Milad Hashemi Mohammad Norouzi Kevin Swersky David Duvenaud 46 71 0 08 Oct 2020
A Neural Network MCMC sampler that maximizes Proposal Entropy Zengyi Li Yubei Chen Friedrich T. Sommer 60 15 0 07 Oct 2020
Denoising Diffusion Implicit Models Jiaming Song Chenlin Meng Stefano Ermon VLM DiffM 140 7,166 0 06 Oct 2020
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models Zhisheng Xiao Karsten Kreis Jan Kautz Arash Vahdat 35 124 0 01 Oct 2020
Rethinking Attention with Performers K. Choromanski Valerii Likhosherstov David Dohan Xingyou Song Andreea Gane ... Afroz Mohiuddin Lukasz Kaiser David Belanger Lucy J. Colwell Adrian Weller 133 1,548 0 30 Sep 2020
Improving the Speed and Quality of GAN by Adversarial Training Jiachen Zhong Xuanqing Liu Cho-Jui Hsieh GAN 27 16 0 07 Aug 2020
NVAE: A Deep Hierarchical Variational Autoencoder Arash Vahdat Jan Kautz BDL 56 900 0 08 Jul 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching Tianyu Pang Kun Xu Chongxuan Li Yang Song Stefano Ermon Jun Zhu DiffM 44 53 0 07 Jul 2020
Gradient Origin Networks Sam Bond-Taylor Chris G. Willcocks BDL DRL 49 18 0 06 Jul 2020
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows Didrik Nielsen P. Jaini Emiel Hoogeboom Ole Winther Max Welling TPM BDL DRL 32 92 0 06 Jul 2020
Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention Angelos Katharopoulos Apoorv Vyas Nikolaos Pappas Franccois Fleuret 105 1,716 0 29 Jun 2020
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression Rianne van den Berg A. Gritsenko Mostafa Dehghani C. Sønderby Tim Salimans 43 60 0 22 Jun 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 284 17,550 0 19 Jun 2020
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains Matthew Tancik Pratul P. Srinivasan B. Mildenhall Sara Fridovich-Keil N. Raghavan Utkarsh Singhal R. Ramamoorthi Jonathan T. Barron Ren Ng 84 2,384 0 18 Jun 2020