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Unifying GANs and Score-Based Diffusion as Generative Particle Models

25 May 2023

Papers citing "Unifying GANs and Score-Based Diffusion as Generative Particle Models"

35 / 35 papers shown

Title
Differentially Private Gradient Flow based on the Sliced Wasserstein Distance Ilana Sebag Muni Sreenivas Pydi Jean-Yves Franceschi Alain Rakotomamonjy Mike Gartrell Jamal Atif Alexandre Allauzen 71 3 0 13 Dec 2023
DiffEdit: Diffusion-based semantic image editing with mask guidance Guillaume Couairon Jakob Verbeek Holger Schwenk Matthieu Cord DiffM 145 509 0 20 Oct 2022
Imagen Video: High Definition Video Generation with Diffusion Models Jonathan Ho William Chan Chitwan Saharia Jay Whang Ruiqi Gao ... Diederik P. Kingma Ben Poole Mohammad Norouzi David J. Fleet Tim Salimans VGen 162 1,540 0 05 Oct 2022
Diffusion-GAN: Training GANs with Diffusion Zhendong Wang Huangjie Zheng Pengcheng He Weizhu Chen Mingyuan Zhou DiffM 67 233 0 05 Jun 2022
Elucidating the Design Space of Diffusion-Based Generative Models Tero Karras M. Aittala Timo Aila S. Laine DiffM 210 2,018 0 01 Jun 2022
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models Alex Nichol Prafulla Dhariwal Aditya A. Ramesh Pranav Shyam Pamela Mishkin Bob McGrew Ilya Sutskever Mark Chen 364 3,627 0 20 Dec 2021
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs Zhisheng Xiao Karsten Kreis Arash Vahdat DiffM 100 558 0 15 Dec 2021
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 138 57 0 04 Dec 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support Pierre Glaser Michael Arbel Arthur Gretton 92 40 0 16 Jun 2021
A Neural Tangent Kernel Perspective of GANs Jean-Yves Franceschi Emmanuel de Bézenac Ibrahim Ayed Mickaël Chen Sylvain Lamprier Patrick Gallinari 79 27 0 10 Jun 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 80 57 0 01 Jun 2021
Large-Scale Wasserstein Gradient Flows Petr Mokrov Alexander Korotin Lingxiao Li Aude Genevay Justin Solomon Evgeny Burnaev 72 75 0 01 Jun 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 263 7,933 0 11 May 2021
Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis Bingchen Liu Yizhe Zhu Kunpeng Song Ahmed Elgammal 229 239 0 12 Jan 2021
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 353 6,566 0 26 Nov 2020
On the linearity of large non-linear models: when and why the tangent kernel is constant Chaoyue Liu Libin Zhu M. Belkin 116 143 0 02 Oct 2020
Adversarial score matching and improved sampling for image generation Alexia Jolicoeur-Martineau Remi Piche-Taillefer Rémi Tachet des Combes Ioannis Mitliagkas DiffM 71 126 0 11 Sep 2020
The limits of min-max optimization algorithms: convergence to spurious non-critical sets Ya-Ping Hsieh P. Mertikopoulos Volkan Cevher 86 83 0 16 Jun 2020
The equivalence between Stein variational gradient descent and black-box variational inference Casey Chu Kentaro Minami Kenji Fukumizu 38 7 0 04 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 65 114 0 12 Mar 2020
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 258 3,954 0 12 Jul 2019
Sliced Score Matching: A Scalable Approach to Density and Score Estimation Yang Song Sahaj Garg Jiaxin Shi Stefano Ermon 115 418 0 17 May 2019
Self-Attention Generative Adversarial Networks Han Zhang Ian Goodfellow Dimitris N. Metaxas Augustus Odena GAN 151 3,731 0 21 May 2018
Stein Variational Gradient Descent as Gradient Flow Qiang Liu OT 86 277 0 25 Apr 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 227 9,560 0 31 Mar 2017
NIPS 2016 Tutorial: Generative Adversarial Networks Ian Goodfellow GAN 175 1,726 0 31 Dec 2016
Unrolled Generative Adversarial Networks Luke Metz Ben Poole David Pfau Jascha Narain Sohl-Dickstein GAN 116 1,004 0 07 Nov 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 76 1,093 0 16 Aug 2016
Gaussian Error Linear Units (GELUs) Dan Hendrycks Kevin Gimpel 174 5,037 0 27 Jun 2016
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization Sebastian Nowozin Botond Cseke Ryota Tomioka GAN 156 1,659 0 02 Jun 2016
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford Luke Metz Soumith Chintala GAN OOD 271 14,023 0 19 Nov 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 465 43,341 0 11 Feb 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 247 8,426 0 28 Nov 2014
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 274 12,458 0 24 Jun 2012
Hilbert space embeddings and metrics on probability measures Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu Bernhard Schölkopf Gert R. G. Lanckriet 217 747 0 30 Jul 2009