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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. Anomalous diffusion - Wikipedia

    en.wikipedia.org/wiki/Anomalous_diffusion

    Anomalous diffusion is a diffusion process with a non-linear ... normal diffusion are not capable of characterizing some complex diffusion processes, for instance ...

  4. Diffusion - Wikipedia

    en.wikipedia.org/wiki/Diffusion

    Diffusion models may also be used to solve inverse boundary value problems in which some information about the depositional environment is known from paleoenvironmental reconstruction and the diffusion equation is used to figure out the sediment influx and time series of landform changes.

  5. 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.

  6. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The normal distribution, also called the Gaussian or the bell curve. It is ubiquitous in nature and statistics due to the central limit theorem: every variable that can be modelled as a sum of many small independent, identically distributed variables with finite mean and variance is approximately normal. The normal-exponential-gamma distribution

  7. 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.

  8. Reaction–diffusion system - Wikipedia

    en.wikipedia.org/wiki/Reaction–diffusion_system

    Reaction–diffusion systems are mathematical models that correspond to several physical phenomena. The most common is the change in space and time of the concentration of one or more chemical substances: local chemical reactions in which the substances are transformed into each other, and diffusion which causes the substances to spread out ...

  9. Bass diffusion model - Wikipedia

    en.wikipedia.org/wiki/Bass_diffusion_model

    There are two special cases of the Bass diffusion model. The first special case occurs when q=0, when the model reduces to the exponential distribution. The second special case reduces to the logistic distribution, when p=0. The Bass model is a special case of the Gamma/shifted Gompertz distribution (G/SG): Bemmaor [9] (1994)