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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.
In particular, experiments on the diffusion of foreign material in a turbulent water stream, [6] vertical structure of water in lake bodies, [7] and lowest part of the atmosphere [8] found experimental evidence that eddy diffusion is indeed stronger than molecular diffusion and generally obeys the theory originally developed by G. I. Taylor ...
A water model is defined by its geometry, together with other parameters such as the atomic charges and Lennard-Jones parameters. In computational chemistry, a water model is used to simulate and thermodynamically calculate water clusters, liquid water, and aqueous solutions with explicit solvent.
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.
the water is of constant density (incompressible), any external loads on the aquifer (e.g., overburden, atmospheric pressure) are constant, for the 1D radial problem the pumping well is fully penetrating a non-leaky aquifer, the groundwater is flowing slowly (Reynolds number less than unity), and; the hydraulic conductivity (K) is an isotropic ...
A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models. [2]
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]
Numerical diffusion is a difficulty with computer simulations of continua (such as fluids) wherein the simulated medium exhibits a higher diffusivity than the true medium. This phenomenon can be particularly egregious when the system should not be diffusive at all, for example an ideal fluid acquiring some spurious viscosity in a numerical model.