stochastic process
C1599
concept
A stochastic process is a collection of random variables indexed by time or space that describes the evolution of a system subject to inherent randomness.
All labels observed (11)
| Label | Occurrences |
|---|---|
| stochastic process canonical | 15 |
| Gaussian process | 2 |
| mean-reverting process | 2 |
| Markov model | 1 |
| class of stochastic processes | 1 |
| cumulative advantage process | 1 |
| law of the iterated logarithm | 1 |
| point process | 1 |
| stationary process | 1 |
| stochastic partial differential equation model | 1 |
| supermartingale | 1 |
Description generation (CDg)
The one-sentence description above was generated by prompting gpt-5.1 with the class name and this instruction.
Instruction
generate a one-sentence description for a given conceptual class. # Response Format Return only the sentence: "Description: [one-sentence description of the conceptional class]"
Input
Class: stochastic process
Generated description
A stochastic process is a collection of random variables indexed by time or space that describes the evolution of a system subject to inherent randomness.
Instances (20)
| Instance | Via concept surface |
|---|---|
| Lévy processes | class of stochastic processes |
| Chinese restaurant process | — |
| Bernoulli trials | — |
|
Wiener
surface form:
Wiener process
|
— |
| Brownian motion | — |
| Kraichnan model of passive scalar advection | stochastic partial differential equation model |
|
OU process
surface form:
Ornstein–Uhlenbeck process
|
— |
| Snell envelope | — |
| Gaussian process | — |
| Khinchin's law of the iterated logarithm | law of the iterated logarithm |
| Ornstein–Uhlenbeck process | — |
|
Markov processes
surface form:
Markov process
|
— |
|
Poisson
surface form:
Poisson process
|
— |
| Poisson process | — |
|
Itô processes
surface form:
Itô process
|
— |
| Kingman’s coalescent | — |
| Matthew effect | cumulative advantage process |
| Hidden Markov Model | Markov model |
| Dyson Brownian motion | — |
| Kac walk | — |