Diffusion processes are continuous-time, continuous-state processes whose sample paths are everywhere continuous but nowhere differentiable. They arise in many natural phenomena and in some sense are generalized versions of the Brownian motion.
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In probability theory and statistics, diffusion processes are a class of continuous-time Markov process with almost surely continuous sample paths.
A diffusion process is a kind of random process. We let Xt be the value of the process at time t. Most interesting diffusions have more than one component:.
A diffusion model consists of three major components: the forward process, the reverse process, and the sampling procedure. The goal of diffusion models is to ...
Diffusion processes are processes where some attribute, like an infectious disease, spreads through a fixed population and the probability of a new individual ...
Both types of anomalous diffusion processes have been recognized to play important roles in various physical, chemical, biological, and geological processes.
The early application of diffusion processes by Fisher, Wright, and Kimura elevated population genetics to one of the more sophisticated branches of applied ...
Mar 1, 2023 · Abstract:We introduce Functional Diffusion Processes (FDPs), which generalize score-based diffusion models to infinite-dimensional function ...
The simplest and most fundamental diffusion process is Brownian motion {B(t)}, which is sometimes called the Wiener process {W(t)}. Definition 1. {B(t)} is ...