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  2. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing artificial intelligence boom .

  3. Fooocus - Wikipedia

    en.wikipedia.org/wiki/Fooocus

    Fooocus is an open source generative artificial intelligence program that allows users to generate images from a text prompt. [3] [4] It uses Stable Diffusion as the base model for its image capabilities as well as a collection of default settings and prompts to make the image generation process more streamlined.

  4. Diffusion model - Wikipedia

    en.wikipedia.org/wiki/Diffusion_model

    Stable Diffusion (2022-08), released by Stability AI, consists of a denoising latent diffusion model (860 million parameters), a VAE, and a text encoder. The denoising network is a U-Net, with cross-attention blocks to allow for conditional image generation.

  5. For teen girls victimized by ‘deepfake’ nude photos, there ...

    www.aol.com/news/teen-girls-victimized-deepfake...

    AI technology is becoming more widely available, such as stable diffusion (open-source technology that can produce images from text prompts) and “face-swap” tools that can put a victim’s ...

  6. Riffusion - Wikipedia

    en.wikipedia.org/wiki/Riffusion

    Riffusion is a neural network, designed by Seth Forsgren and Hayk Martiros, that generates music using images of sound rather than audio. [1] It was created as a fine-tuning of Stable Diffusion, an existing open-source model for generating images from text prompts, on spectrograms. [1]

  7. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  8. Autoencoder - Wikipedia

    en.wikipedia.org/wiki/Autoencoder

    An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.

  9. Diffusion map - Wikipedia

    en.wikipedia.org/wiki/Diffusion_map

    Diffusion maps is a dimensionality reduction or feature extraction algorithm introduced by Coifman and Lafon [1 ... By integrating local similarities at different ...