Deep Unsupervised Learning using Nonequilibrium Thermodynamics ​

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Authors: Laurent Dinh, David Krueger, Yoshua Bengio
Year: 2015
Journal: NeurIPS
DOI: 10.48550/arXiv.1503.03585
Publisher: https://arxiv.org/abs/1503.03585

Keywords: diffusion, generative model

Abstract ​

We develop a generic and learnable framework for efficient unrestricted sampling from a broad family of probability distributions.

Cite this paper ​

@misc{dmorig2015,
  title  = {Deep Unsupervised Learning using Nonequilibrium Thermodynamics},
  author = {Laurent Dinh, David Krueger, Yoshua Bengio},
  year   = {2015},
  journal = {NeurIPS},
  doi    = {10.48550/arXiv.1503.03585},
  url    = {https://doi.org/10.48550/arXiv.1503.03585},
}

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