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Generative models based on diffusion have become the state of the art in the last few years, notably for image generation.
Reverse-time diffusion equation models
Brian DO Anderson · 1982
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A class of wasserstein metrics for probability distributions
Clark R Givens and Rae Michael Shortt · 1984
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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From non-ergodic eigenvectors to local resolvent statistics and back: A random matrix perspective
Davide Facoetti, Pierpaolo Vivo, and Giulio Biroli · 2016
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The total variation distance between high-dimensional gaussians with the same mean
Luc Devroye, Abbas Mehrabian, and Tommy Reddad · 2018
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Statistical aspects of wasserstein distances
Victor M Panaretos and Yoav Zemel · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Non-ergodic delocalization in the rosenzweig–porter model
Per von Soosten and Simone Warzel · 2019
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Eigenvectors distribution and quantum unique ergodicity for deformed wigner matrices, 2020
Lucas Benigni · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Diffusion schrödinger bridge with applications to score-based generative modeling
Valentin De Bortoli, James Thornton, Jeremy Heng, and Arnaud Doucet · 2021
Cited alongside, same era.
Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
Later among the works it cites.
Convergence of denoising diffusion models under the manifold hypothesis
Valentin De Bortoli · 2022
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Wavelet score-based generative modeling, 2022
Florentin Guth, Simon Coste, Valentin De Bortoli, and Stephane Mallat · 2022
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Convergence for score-based generative modeling with polynomial complexity
Holden Lee, Jianfeng Lu, and Yixin Tan · 2022
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Diffusion models: A comprehensive survey of methods and applications
Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang, Bin Cui, and Ming-Hsuan Yang · 2022
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