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9
201 Metadata/My Library.bib
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@ -11227,6 +11227,15 @@ Subject\_term: Careers, Politics, Policy},
isbn = {1-4612-0577-8}
}
@online{SoraCreatingVideo,
title = {Sora: {{Creating}} Video from Text},
shorttitle = {Sora},
url = {https://openai.com/index/sora/},
urldate = {2024-10-30},
langid = {american},
file = {/home/danesabo/Zotero/storage/YUQHRZUS/sora.html}
}
@misc{sorensenLecturesCurryHowardIsomorphism,
title = {Lectures on the {{Curry-Howard Isomorphism}}},
author = {Sorensen, Morten Heine B. and Urzyczyn, Pawel},

2
4 Qualifying Exam/2 Writing/3. QE Research Approach.md
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@ -43,4 +43,4 @@ Something to justify, why diffusion model as opposed to other generative AI
## Writin some stuff
The purpose of this proposal is to suggest that using a generative network to create unstructured perturbations can be a viable way to advance the state of the art. But to do this, the current state of diffusion models and their place must be introduced. The generative diffusion model is a recent breakthrough in generative models. Diffusion models
The purpose of this proposal is to suggest that using a generative network to create unstructured perturbations can be a viable way to advance the state of the art. But to do this, the current state of diffusion models and their place must be introduced. The generative diffusion model is a recent breakthrough in generative models [@sohl-dicksteinDeepUnsupervisedLearning2015]. Diffusion generative models are the state of the art for image and video generation, and have demonstrated promise for audio generation and noise removal [@kongDiffWaveVersatileDiffusion2020] [@SoraCreatingVideo]. Diffusion models do this through a forward noise-inducing process, and a backwards