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In the realm of Artificial Intelligence Generated Content (AIGC), flow-matching models have emerged as a powerhouse, achieving success due to their robust theoretical underpinnings and solid ability for large-scale generative modeling.
The CIFAR-10 Dataset
Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton · 2014
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Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu · 2016
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GANs trained by a two time-scale update rule converge to a local Nash equilibrium
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Neural Ordinary Differential Equations
Ricky TQ Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018
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Will Grathwohl, Ricky TQ Chen, Jesse Bettencourt, Ilya Sutskever, and David Duvenaud · 2018
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Durk P Kingma and Prafulla Dhariwal · 2018
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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Residual flows for invertible generative modeling
Ricky TQ Chen, Jens Behrmann, David K Duvenaud, and Jörn-Henrik Jacobsen · 2019
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Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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A multi-class hinge loss for conditional gans
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Knowledge distillation in iterative generative models for improved sampling speed
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Sdedit: Image synthesis and editing with stochastic differential equations
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Improved denoising diffusion probabilistic models
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Tackling the generative learning trilemma with denoising diffusion gans
Zhisheng Xiao, Karsten Kreis, and Arash Vahdat · 2021
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Building normalizing flows with stochastic interpolants
Michael S Albergo and Eric Vanden-Eijnden · 2022
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Diffedit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord · 2022
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Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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Equivariant diffusion for molecule generation in 3d
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Heeseung Kim, Sungwon Kim, and Sungroh Yoon · 2022
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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and Qiang Liu · 2022
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On distillation of guided diffusion models
Chenlin Meng, Ruiqi Gao, Diederik P Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans · 2022
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Deep equilibrium approaches to diffusion models
Ashwini Pokle, Zhengyang Geng, and J Zico Kolter · 2022
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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2022
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Hierarchical text-conditional image generation with clip latents
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Truncated diffusion probabilistic models and diffusion-based adversarial auto-encoders
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Video generation models as world simulators
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Flash diffusion: Accelerating any conditional diffusion model for few steps image generation
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Daniel Watson, William Chan, Jonathan Ho, and Mohammad Norouzi · 2022
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Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, and Anima Anandkumar · 2022
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Consistency flow matching: Defining straight flows with velocity consistency
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Diffusion models are innate one-step generators
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