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Stable Diffusion 3 (2024-03) [65] changed the latent diffusion model from the UNet to a Transformer model, and so it is a DiT. It uses rectified flow. It uses rectified flow. Stable Video 4D (2024-07) [ 66 ] is a latent diffusion model for videos of 3D objects.
Diffusion of innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology spread. The theory was popularized by Everett Rogers in his book Diffusion of Innovations , first published in 1962. [ 1 ]
The sociological theory of diffusion is the study of the diffusion of innovations throughout social groups and organizations. The topic has seen rapid growth since the 1990s, reflecting curiosity about the process of social change and "fueled by interest in institutional arguments and in network and dynamic analysis."
Crossing the Chasm is an adaptation of an innovation-adoption model called diffusion of innovations theory created by Everett Rogers, The author argues there is a chasm between the early adopters of the product (the technology enthusiasts and visionaries) and the early majority (the pragmatists).
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 more pessimistic picture of the future than alternative model(s) such as the Weibull distribution and the shifted Gompertz distribution.
Everett M. "Ev" Rogers (March 6, 1931 – October 21, 2004) was an American communication theorist and sociologist, who originated the diffusion of innovations theory and introduced the term early adopter.
The technology adoption lifecycle is a sociological model that is an extension of an earlier model called the diffusion process, which was originally published in 1956 by George M. Beal and Joe M. Bohlen. [1]
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.