Gaussian process - определение. Что такое Gaussian process
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Что (кто) такое Gaussian process - определение


Gaussian process         
  • Autocorrelation of a random lacunary Fourier series
  • Gaussian Process Regression (prediction) with a squared exponential kernel. Left plot are draws from the prior function distribution. Middle are draws from the posterior. Right is mean prediction with one standard deviation shaded.
  • The effect of choosing different kernels on the prior function distribution of the Gaussian process. Left is a squared exponential kernel. Middle is Brownian. Right is quadratic.
STOCHASTIC PROCESS SUCH THAT EVERY FINITE COLLECTION OF RANDOM VARIABLES HAS A MULTIVARIATE NORMAL DISTRIBUTION
Gaussian stochastic process; Gaussian processes; Gaussian Process; Gaussian Processes; Applications of Gaussian processes; Bayesian Kernel Ridge Regression
In probability theory and statistics, a Gaussian process is a stochastic process (a collection of random variables indexed by time or space), such that every finite collection of those random variables has a multivariate normal distribution, i.e.
Neural network Gaussian process         
  • An NNGP is derived which is equivalent to a Bayesian neural network with this fully connected architecture.
  • When parameters <math>\theta</math> of an infinite width network are sampled repeatedly from their prior <math>p(\theta)</math>, the resulting distribution over network outputs is described by a Gaussian process.
MODELING TOOL FOR ASSIGNING PROBABILITIES TO EVENTS
Draft:Neural Network Gaussian Process; Neural Network Gaussian Process
Bayesian networks are a modeling tool for assigning probabilities to events, and thereby characterizing the uncertainty in a model's predictions. Deep learning and artificial neural networks are approaches used in machine learning to build computational models which learn from training examples.
Q-Gaussian process         
q-Gaussian processes are deformations of the usual Gaussian distribution. There are several different versions of this; here we treat a multivariate deformation, also addressed as q-Gaussian process, arising from free probability theory and corresponding to deformations of the canonical commutation relations.