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  2. Diffusion model - Wikipedia

    en.wikipedia.org/wiki/Diffusion_model

    The goal of diffusion models is to learn a diffusion process for a given dataset, such that the process can generate new elements that are distributed similarly as the original dataset. A diffusion model models data as generated by a diffusion process, whereby a new datum performs a random walk with drift through the space of all possible data. [2]

  3. Latent diffusion model - Wikipedia

    en.wikipedia.org/wiki/Latent_Diffusion_Model

    The Latent Diffusion Model (LDM) [1] is a diffusion model architecture developed by the CompVis (Computer Vision & Learning) [2] group at LMU Munich. [3]Introduced in 2015, diffusion models (DMs) are trained with the objective of removing successive applications of noise (commonly Gaussian) on training images.

  4. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Diagram of the latent diffusion architecture used by Stable Diffusion The denoising process used by Stable Diffusion. The model generates images by iteratively denoising random noise until a configured number of steps have been reached, guided by the CLIP text encoder pretrained on concepts along with the attention mechanism, resulting in the desired image depicting a representation of the ...

  5. Bass diffusion model - Wikipedia

    en.wikipedia.org/wiki/Bass_diffusion_model

    The rapid, recent (as of early 2007) growth in online social networks (and other virtual communities) has led to an increased use of the Bass diffusion model. The Bass diffusion model is used to estimate the size and growth rate of these social networks. The work by Christian Bauckhage and co-authors [10] shows that the Bass model provides a ...

  6. Diffusion process - Wikipedia

    en.wikipedia.org/wiki/Diffusion_process

    In probability theory and statistics, diffusion processes are a class of continuous-time Markov process with almost surely continuous sample paths. Diffusion process is stochastic in nature and hence is used to model many real-life stochastic systems.

  7. ComfyUI - Wikipedia

    en.wikipedia.org/wiki/ComfyUI

    ComfyUI is an open source, node-based program that allows users to generate images from a series of text prompts.It uses free diffusion models such as Stable Diffusion as the base model for its image capabilities combined with other tools such as ControlNet and LCM Low-rank adaptation with each tool being represented by a node in the program.

  8. Text-to-image model - Wikipedia

    en.wikipedia.org/wiki/Text-to-image_model

    An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.

  9. 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.

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