References

GenSBI is inspired by and builds upon a broad body of research in simulation-based inference, flow matching, and diffusion models. Below are key libraries and papers that have influenced the development of this project.

If you use GenSBI, please consider citing these works, which provide the theoretical foundations and methodologies implemented in this library.

How to cite GenSBI

If you use GenSBI in your research, please cite:

@misc{GenSBI,
	author       = {Amerio, Aurelio},
	title        = "{GenSBI: Generative models for Simulation-Based Inference}",
	year         = {2025}, 
	publisher    = {GitHub},
	journal      = {GitHub repository},
	howpublished = {\url{https://github.com/aurelio-amerio/GenSBI}}
}

Foundational Papers

If you are using specific methodologies from GenSBI, please also consider citing the following foundational papers:

Flow Matching for Generative Modeling

@misc{lipman2023flowmatchinggenerativemodeling,
      title={Flow Matching for Generative Modeling},
      author={Yaron Lipman and Ricky T. Q. Chen and Heli Ben-Hamu and Maximilian Nickel and Matt Le},
      year={2023},
      eprint={2210.02747},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2210.02747},
}

Score-Based Generative Modeling through Stochastic Differential Equations

@misc{song2021scorebasedgenerativemodelingstochastic,
      title={Score-Based Generative Modeling through Stochastic Differential Equations},
      author={Yang Song and Jascha Sohl-Dickstein and Diederik P. Kingma and Abhishek Kumar and Stefano Ermon and Ben Poole},
      year={2021},
      eprint={2011.13456},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2011.13456},
}

Elucidating the Design Space of Diffusion-Based Generative Models

@misc{karras2022elucidatingdesignspacediffusionbased,
      title={Elucidating the Design Space of Diffusion-Based Generative Models},
      author={Tero Karras and Miika Aittala and Timo Aila and Samuli Laine},
      year={2022},
      eprint={2206.00364},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2206.00364},
}

All-in-one simulation-based inference

@misc{gloeckler2024allinonesimulationbasedinference,
      title={All-in-one simulation-based inference},
      author={Manuel Gloeckler and Michael Deistler and Christian Weilbach and Frank Wood and Jakob H. Macke},
      year={2024},
      eprint={2404.09636},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2404.09636},
}

FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space

@misc{labs2025flux1kontextflowmatching,
      title={FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space},
      author={Black Forest Labs and Stephen Batifol and Andreas Blattmann and Frederic Boesel and Saksham Consul and Cyril Diagne and Tim Dockhorn and Jack English and Zion English and Patrick Esser and Sumith Kulal and Kyle Lacey and Yam Levi and Cheng Li and Dominik Lorenz and Jonas Müller and Dustin Podell and Robin Rombach and Harry Saini and Axel Sauer and Luke Smith},
      year={2025},
      eprint={2506.15742},
      archivePrefix={arXiv},
      primaryClass={cs.GR},
      url={https://arxiv.org/abs/2506.15742},
}