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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. Diffusion processes are stochastic in nature and hence are used to model many real-life stochastic systems. Brownian motion, reflected Brownian motion and Ornstein–Uhlenbeck processes are examples of…
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Diffusion process | is a | Markov process with continuous sample paths for which the Kolmogorov forward equation is the Fokker | 0.90 | text |
| Diffusion process | related to Mathematical definition | Markov | 0.60 | section |
| Diffusion process | related to Mathematical definition | Kolmogorov | 0.60 | section |
| Diffusion process | related to Mathematical definition | Fokker | 0.60 | section |
| Diffusion process | related to Mathematical definition | Planck | 0.60 | section |
| Diffusion process | related to Mathematical definition | Let | 0.60 | section |
| Diffusion process | related to Mathematical definition | Borel | 0.60 | section |
| Diffusion process | related to Mathematical definition | There | 0.60 | section |
| Diffusion process | related to Mathematical definition | Omega | 0.60 | section |
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