{{keywords>GAN, image generation}}

<title classes #id>
Topics not Covered in this Book
</title>

===== Image Generation =====

  * [[https://developers.google.com/machine-learning/gan/gan_structure|GAN]] by Google
  * [[https://arxiv.org/abs/1809.11096|Large Scale GAN Training for High Fidelity Natural Image Synthesis]] by Brock et al (2018)
  * [[https://arxiv.org/abs/1802.05751|Image Transformer]] by Parmar et all (2018)
  * [[https://jalammar.github.io/illustrated-stable-diffusion/|The Illustrated Stable Diffusion]] by Jay Alammar
  * [[https://www.matthewtancik.com/nerf|NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis]] by Mildenhall et all (2020)
  * [[https://arxiv.org/abs/1802.05751|Nerfies: Deformable Neural Radiance Fields]] by Park et al (2021)

===== Text Generation =====

  * [[https://arxiv.org/abs/2203.02155|Training language models to follow instructions with human feedback]] by Ouyang et all (2022) (The InstructGPT paper)
  * [[https://blog.matdmiller.com/posts/2023-06-10_transformers/notebook.html|Transformers From Scratch]] by Mat Miller (2024)

===== Neural Network Best Practices and Tricks =====

  * [[https://github.com/huggingface/peft|PEFT: State-of-the-art Parameter-Efficient Fine-Tuning methods]] by Hugging Face
  * [[https://www.philschmid.de/fine-tune-llms-in-2024-with-trl|How to Fine-Tune LLMs in 2024 with Hugging Face]] by Philipp Schmid (2024)
  * [[https://towardsdatascience.com/merge-large-language-models-with-mergekit-2118fb392b54|Merge Large Language Models with mergekit]] by Maxime Labonne (2024)