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@book{goodfellow2016deep,
  title={Deep learning},
  author={Goodfellow, Ian and Bengio, Yoshua and Courville, Aaron and Bengio, Yoshua},
  volume={1},
  year={2016},
  publisher={MIT Press}
}

@article{yang2023diffusion,
  title={Diffusion models: A comprehensive survey of methods and applications},
  author={Yang, Ling and Zhang, Zhilong and Song, Yang and Hong, Shenda and Xu, Runsheng and Zhao, Yue and Zhang, Wentao and Cui, Bin and Yang, Ming-Hsuan},
  journal={ACM Computing Surveys},
  volume={56},
  number={4},
  pages={1--39},
  year={2023},
  publisher={ACM New York, NY, USA}
}

@inproceedings{ddpm,
 author = {Ho, Jonathan and Jain, Ajay and Abbeel, Pieter},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
 pages = {6840--6851},
 publisher = {Curran Associates, Inc.},
 title = {Denoising Diffusion Probabilistic Models},
 url = {https://proceedings.neurips.cc/paper/2020/file/4c5bcfec8584af0d967f1ab10179ca4b-Paper.pdf},
 volume = {33},
 year = {2020}
}

@inproceedings{vae,
  added-at = {2020-10-15T14:36:56.000+0200},
  author = {Kingma, Diederik P. and Welling, Max},
  biburl = {https://www.bibsonomy.org/bibtex/242e5be6faa01cba2587f4907ac99dce8/annakrause},
  booktitle = {2nd International Conference on Learning Representations, {ICLR} 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings},
  eprint = {http://arxiv.org/abs/1312.6114v10},
  eprintclass = {stat.ML},
  eprinttype = {arXiv},
  file = {:http\://arxiv.org/pdf/1312.6114v10:PDF;:KingmaWelling_Auto-EncodingVariationalBayes.pdf:PDF},
  interhash = {a626a9d77a123c52405a08da983203cb},
  intrahash = {42e5be6faa01cba2587f4907ac99dce8},
  keywords = {cs.LG stat.ML vae},
  timestamp = {2021-02-01T17:13:18.000+0100},
  title = {{Auto-Encoding Variational Bayes}},
  year = 2014
}

@inproceedings{gan,
 author = {Goodfellow, Ian and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {Z. Ghahramani and M. Welling and C. Cortes and N. Lawrence and K.Q. Weinberger},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Generative Adversarial Nets},
 url = {https://proceedings.neurips.cc/paper/2014/file/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf},
 volume = {27},
 year = {2014}
}

@InProceedings{pmlr-v37-sohl-dickstein15,
  title =   {Deep Unsupervised Learning using Nonequilibrium Thermodynamics},
  author =   {Sohl-Dickstein, Jascha and Weiss, Eric and Maheswaranathan, Niru and Ganguli, Surya},
  booktitle =   {Proceedings of the 32nd International Conference on Machine Learning},
  pages =   {2256--2265},
  year =   {2015},
  editor =   {Bach, Francis and Blei, David},
  volume =   {37},
  series =   {Proceedings of Machine Learning Research},
  address =   {Lille, France},
  month =   {07--09 Jul},
  publisher =    {PMLR}
}

@inproceedings{
edm,
title={Elucidating the Design Space of Diffusion-Based Generative Models},
author={Tero Karras and Miika Aittala and Timo Aila and Samuli Laine},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
url={https://openreview.net/forum?id=k7FuTOWMOc7}
}

@misc{kotelnikov2022tabddpm,
      title={TabDDPM: Modelling Tabular Data with Diffusion Models},
      author={Akim Kotelnikov and Dmitry Baranchuk and Ivan Rubachev and Artem Babenko},
      year={2022},
      eprint={2209.15421},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}


@Article{Tiago2024ADT,
 author = {Cristiana Tiago and S. Snare and Jurica Šprem and K. Mcleod},
 booktitle = {IEEE Access},
 journal = {IEEE Access},
 pages = {17594-17602},
 title = {A Domain Translation Framework With an Adversarial Denoising Diffusion Model to Generate Synthetic Datasets of Echocardiography Images},
 volume = {11},
 year = {2024}
}


@Article{Gulrajani2017ImprovedTO,
 author = {Ishaan Gulrajani and Faruk Ahmed and Martín Arjovsky and Vincent Dumoulin and Aaron C. Courville},
 booktitle = {Neural Information Processing Systems},
 pages = {5767-5777},
 title = {Improved Training of Wasserstein GANs},
 year = {2017}
}


@Article{Song2020ScoreBasedGM,
 author = {Yang Song and Jascha Narain Sohl-Dickstein and Diederik P. Kingma and Abhishek Kumar and Stefano Ermon and Ben Poole},
 booktitle = {International Conference on Learning Representations},
 journal = {ArXiv},
 title = {Score-Based Generative Modeling through Stochastic Differential Equations},
 volume = {abs/2011.13456},
 year = {2020}
}