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Make-A-Video (2022) is a text-to-video diffusion model. [73] [74] CM3leon (2023) is not a diffusion model, but an autoregressive causally masked Transformer, with mostly the same architecture as LLaMa-2. [75] [76] Transfusion architectural diagram. Transfusion (2024) is a Transformer that combines autoregressive text generation and denoising ...
Diffusion process is stochastic in nature and hence is used to model many real-life stochastic systems. ... A diffusion process is a Markov process with continuous ...
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.
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 .
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 ...
The Maxwell–Stefan diffusion (or Stefan–Maxwell diffusion) is a model for describing diffusion in multicomponent systems. The equations that describe these transport processes have been developed independently and in parallel by James Clerk Maxwell [ 1 ] for dilute gases and Josef Stefan [ 2 ] for liquids.
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The drift-diffusion model (DDM) is a well defined [19] model, that is proposed to implement an optimal decision policy for 2AFC. [20] It is the continuous analog of a random walk model. [ 7 ] The DDM assumes that in a 2AFC task, the subject is accumulating evidence for one or other of the alternatives at each time step, and integrating that ...