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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 machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling. [1] It is part of the families of probabilistic graphical models and variational Bayesian methods .
After training to convergence, it can be used for image generation by starting with an image composed of random noise, and applying the network iteratively to denoise the image. Diffusion-based image generators have seen widespread commercial interest, such as Stable Diffusion and DALL-E. These models typically combine diffusion models with ...
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.
Displacement ventilation is best suited for taller spaces (higher than 3 meters [10 feet]). [2] Standard mixing ventilation may be better suited for smaller spaces where air quality is not as great a concern, such as single-occupant offices, and where the room height is not tall (e.g., lower than 2.3 meters [7.5 feet]).
A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, [1] [2] [3] which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.
A round diffuser in an HVAC system. Diffusers are very common in heating, ventilating, and air-conditioning systems. [3] Diffusers are used in both all-air and air-water HVAC systems, as part of room air distribution subsystems, and serve several purposes: To deliver both conditioning and ventilating air
MILES was introduced to the U.S. Army for direct-fire, force-on-force training capability at home stations and combat training centers during operational testing in 1978 and 1979 following the conclusion of the US Army's Engineering Development program awarded to Xerox Electro-Optical Systems. The goal of the program was to design and build a ...