VCT: Training Consistency Models with Variational Noise Coupling

25 February 2025

Papers citing "VCT: Training Consistency Models with Variational Noise Coupling"

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Title
Training Latent Diffusion Models with Interacting Particle Algorithms Tim Y. J. Wang Juan Kuntz O. Deniz Akyildiz 61 0 0 18 May 2025
The Curse of Conditions: Analyzing and Improving Optimal Transport for Conditional Flow-Based Generation Ho Kei Cheng Alexander Schwing OT 95 1 0 13 Mar 2025
Truncated Consistency Models Sangyun Lee Yilun Xu Tomas Geffner Giulia Fanti Karsten Kreis Arash Vahdat Weili Nie 108 3 0 18 Oct 2024
Simple ReFlow: Improved Techniques for Fast Flow Models Beomsu Kim Yu-Guan Hsieh Michal Klein Marco Cuturi Jong Chul Ye Bahjat Kawar James Thornton VLM 72 10 0 10 Oct 2024
Consistency Flow Matching: Defining Straight Flows with Velocity Consistency Ling Yang Zixiang Zhang Zhilong Zhang Xingchao Liu Minkai Xu Wentao Zhang Chenlin Meng Stefano Ermon Bin Cui 58 21 0 02 Jul 2024
Consistency Models Made Easy Zhengyang Geng Ashwini Pokle William Luo Justin Lin J. Zico Kolter 79 29 0 20 Jun 2024
Improving Consistency Models with Generator-Augmented Flows Thibaut Issenhuth Sangchul Lee Jean-Yves Franceschi Jean-Yves Franceschi Chansoo Kim Alain Rakotomamonjy 29 1 0 13 Jun 2024
EM Distillation for One-step Diffusion Models Sirui Xie Zhisheng Xiao Diederik P. Kingma Tingbo Hou Ying Nian Wu Kevin Patrick Murphy Tim Salimans Ben Poole Ruiqi Gao VLM DiffM 64 28 0 27 May 2024
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling Grigory Bartosh Dmitry Vetrov C. A. Naesseth DiffM 65 16 0 19 Apr 2024
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation Mingyuan Zhou Huangjie Zheng Zhendong Wang Mingzhang Yin Hai Huang DiffM 64 62 0 05 Apr 2024
Multistep Consistency Models Jonathan Heek Emiel Hoogeboom Tim Salimans 40 36 0 11 Mar 2024
Analyzing and Improving the Training Dynamics of Diffusion Models Tero Karras M. Aittala J. Lehtinen Janne Hellsten Timo Aila S. Laine 99 189 0 05 Dec 2023
One-step Diffusion with Distribution Matching Distillation Tianwei Yin Michael Gharbi Richard Zhang Eli Shechtman Frédo Durand William T. Freeman Taesung Park DiffM 154 261 0 30 Nov 2023
DiffEnc: Variational Diffusion with a Learned Encoder Beatrix M. G. Nielsen Anders Christensen Andrea Dittadi Ole Winther DiffM 61 13 0 30 Oct 2023
Improved Techniques for Training Consistency Models Yang Song Prafulla Dhariwal 68 173 0 22 Oct 2023
Neural Diffusion Models Grigory Bartosh Dmitry Vetrov C. A. Naesseth DiffM 44 10 0 12 Oct 2023
Stochastic interpolants with data-dependent couplings M. S. Albergo Mark Goldstein Nicholas M. Boffi Rajesh Ranganath Eric Vanden-Eijnden OT 50 32 0 05 Oct 2023
Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion Dongjun Kim Chieh-Hsin Lai Wei-Hsiang Liao Naoki Murata Yuhta Takida Toshimitsu Uesaka Yutong He Yuki Mitsufuji Stefano Ermon DiffM 70 189 0 01 Oct 2023
Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models Weijian Luo Tianyang Hu Shifeng Zhang Jiacheng Sun Zhenguo Li Zhihua Zhang 64 129 0 29 May 2023
Multisample Flow Matching: Straightening Flows with Minibatch Couplings Aram-Alexandre Pooladian Heli Ben-Hamu Carles Domingo-Enrich Brandon Amos Y. Lipman Ricky T. Q. Chen 75 144 0 28 Apr 2023
TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation David Berthelot Arnaud Autef Jierui Lin Dian Ang Yap Shuangfei Zhai Siyuan Hu Daniel Zheng Walter Talbot Eric Gu DiffM 68 90 0 07 Mar 2023
Consistency Models Yang Song Prafulla Dhariwal Mark Chen Ilya Sutskever VLM DiffM 97 946 0 02 Mar 2023
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models Yilun Xu Ziming Liu Yonglong Tian Shangyuan Tong Max Tegmark Tommi Jaakkola AI4CE DiffM 54 72 0 08 Feb 2023
Improving and generalizing flow-based generative models with minibatch optimal transport Alexander Tong Kilian Fatras Nikolay Malkin G. Huguet Yanlei Zhang Jarrid Rector-Brooks Guy Wolf Yoshua Bengio OOD DiffM OT 95 288 0 01 Feb 2023
Minimizing Trajectory Curvature of ODE-based Generative Models Sangyun Lee Beomsu Kim Jong Chul Ye 83 60 0 27 Jan 2023
Fast Sampling of Diffusion Models via Operator Learning Hongkai Zheng Weili Nie Arash Vahdat Kamyar Azizzadenesheli Anima Anandkumar DiffM 90 144 0 24 Nov 2022
Flow Matching for Generative Modeling Y. Lipman Ricky T. Q. Chen Heli Ben-Hamu Maximilian Nickel Matt Le OOD 174 1,274 0 06 Oct 2022
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow Xingchao Liu Chengyue Gong Qiang Liu OOD 166 988 0 07 Sep 2022
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps Cheng Lu Yuhao Zhou Fan Bao Jianfei Chen Chongxuan Li Jun Zhu DiffM 174 1,403 0 02 Jun 2022
Elucidating the Design Space of Diffusion-Based Generative Models Tero Karras M. Aittala Timo Aila S. Laine DiffM 156 1,952 0 01 Jun 2022
Video Diffusion Models Jonathan Ho Tim Salimans Alexey A. Gritsenko William Chan Mohammad Norouzi David J. Fleet DiffM VGen 163 1,597 0 07 Apr 2022
Pseudo Numerical Methods for Diffusion Models on Manifolds Luping Liu Yi Ren Zhijie Lin Zhou Zhao DiffM 90 644 0 20 Feb 2022
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 351 15,373 0 20 Dec 2021
Score-based Generative Modeling in Latent Space Arash Vahdat Karsten Kreis Jan Kautz DiffM 45 677 0 10 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 68 223 0 28 May 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 178 7,765 0 11 May 2021
Preventing Oversmoothing in VAE via Generalized Variance Parameterization Yuhta Takida Wei-Hsiang Liao Chieh-Hsin Lai Toshimitsu Uesaka Shusuke Takahashi Yuki Mitsufuji DRL 56 14 0 17 Feb 2021
Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed Eric Luhman Troy Luhman DiffM 224 274 0 07 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 292 6,409 0 26 Nov 2020
A Contrastive Learning Approach for Training Variational Autoencoder Priors J. Aneja Alex Schwing Jan Kautz Arash Vahdat DRL 59 84 0 06 Oct 2020
Denoising Diffusion Implicit Models Jiaming Song Chenlin Meng Stefano Ermon VLM DiffM 208 7,294 0 06 Oct 2020
DiffWave: A Versatile Diffusion Model for Audio Synthesis Zhifeng Kong Ming-Yu Liu Jiaji Huang Kexin Zhao Bryan Catanzaro DiffM BDL 110 1,449 0 21 Sep 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 482 17,888 0 19 Jun 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 321 10,591 0 17 Feb 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 181 1,687 0 05 Dec 2019
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 529 10,540 0 12 Dec 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 341 5,081 0 19 Jun 2018
Distribution Matching in Variational Inference Mihaela Rosca Balaji Lakshminarayanan S. Mohamed GAN CML DRL 56 98 0 19 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 246 8,856 0 25 Aug 2017
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 252 6,887 0 12 Mar 2015