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Score-based generative models (SGMs) sample from a target distribution by iteratively transforming noise using the score function of the perturbed target.
On the theory of stochastic processes, with particular reference to applications
William Feller · 1949
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An empirical bayes estimator of the mean of a normal population
Koichi Miyasawa · 1961
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Diffusion processes
Daniel W Stroock and SR Srinivasa Varadhan · 1972
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Estimation of non-normalized statistical models by score matching
Aapo Hyvärinen and Peter Dayan · 2005
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2010
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Least squares estimation without priors or supervision
Martin Raphan and Eero P Simoncelli · 2011
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A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
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Auto-encoding variational bayes
Diederik P Kingma · 2013
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Deep learning face attributes in the wild
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Optimal transport for applied mathematicians
Filippo Santambrogio · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
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Improved techniques for training gans
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Decoupled weight decay regularization
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Demystifying MMD GANs
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Log hyperbolic cosine loss improves variational auto-encoder, 2019
Pengfei Chen, Guangyong Chen, and Shengyu Zhang · 2019
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On the spectral bias of neural networks
Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred Hamprecht, Yoshua Bengio, and Aaron Courville · 2019
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Polyscope, 2019
Nicholas Sharp et al · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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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
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Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Quinn Nichol · 2021
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
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Convergence of score-based generative modeling for general data distributions
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Score-based generative modeling secretly minimizes the wasserstein distance
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