The gaussian-process tag has no wiki summary.
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How to test if two samples are distributed from the same Gaussian process
Given a sequence $\mathbf{x} = (x_1,x_2,\dots,x_n)$ which is sampled from some Gaussian process $GP(\mu_1,\Sigma_1)$ and a "target" sequence $\mathbf{y} = (y_1,y_2,\dots,y_n)$ sampled from another ...
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Gaussian process predictor
I am building GP regressor , my input data is 1-d column vector and so is my target. I have divided my data into training and testing sets. I trained the model to learn the hyper-paramters and then ...
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Confusion related to a derivation
I was reading this paper http://cs.ru.nl/~perry/publications/2011/ICANN2011/groot-icann2011.pdf and I am a bit confused how this was derived
$p(f|Y) \propto p(f)*p(Y|f) \propto ...
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Confusion related to calculation of likelihood
I was reading this paper related to Learning from multiple annotator using Gaussian processes. The idea is if we don't have the actual ground truth of a certain data, but only the labels from some ...
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Combining normal distributions
Imagine that I take two separate measures and I get two separate normal distributions
N1(m1, s1^2)
N2(m2, s2^2)
How can I find a single normal distribution N3 ...
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Estimating a 1-D Brownian motion process using noisy observations
This question is a follow-up on my previous question.
Suppose I have a Brownian motion process that is defined as follows: at time $i=1$ random variable $X_1\sim\mathbf{N}(\mu,\sigma^2)$, and, for ...
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How to implement multiple GP submodels in PYMC
I'm hoping someone can give me some guidance on implementing
Gaussian processes (GP) with PYMC. In particular, I'm not sure how to use
multiple GP submodels properly within a single pymc model.
More ...
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Confusion related to kriging
I was going through the wiki article related to kriging http://en.wikipedia.org/wiki/Kriging. However, I couldn't follow some derivations.
In the first figure for simple kriging, how come the ...
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133 views
Gaussian process - dimensionality reduction
Specific question on Gaussian Processes and dimensionality reduction. I saw a a method for dimensionality reduction for the squared exponential covariance function (not ARD) whereby one uses a GxD ...
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56 views
With what probability the standard deviation of GP capture the measurement?
An interesting property of Gaussian Processes is estimating the uncertainty range. This uncertainty range of prediction can potentially capture the actual measurements.
I am wondering, how many times ...
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133 views
Guassian Process Regression - feature selection
I'm using guassian process regression to do some modeling. One issue I'm encountering is feature selection for some of my models, which often have many relevant features. I'm not sure what the best ...
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115 views
Inferring a Gaussian from noisy data
Assume a noise comes from a specific point on a line, noise which I can detect but not completely accurately. My uncertainty we assume to be Gaussian.
I want to gather evidence about the real ...
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Similarity matrix and multiple-regression
Let, $S_{n*n}$ represent a similarity matrix, among $n$ observation, my case n = 215. and $Y=\{y_1, y_2, ...,y_n\}$ contains a response value for each $x_n$ observation. For each observation we have ...
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Closed form Karhunen-Loeve/PCA expansion for gaussian/squared-exponential covariance
The Gaussian, or squared exponential covariance is $k_{SE}(s,t) = \exp \left\{ -\frac{1}{2l} (s - t)^2 \right\}$. It is a common covariance function used in Gaussian processes. The Karhunen-Loeve ...
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35 views
Confusion related to derivation of gaussian process regression
I was going through these slides related to gaussian process regression and I have a certain confusion
http://www.eurandom.tue.nl/events/workshops/2010/YESIV/Prog-Abstr_files/Ghahramani-lecture2.pdf
...
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63 views
Time derivative of a gaussian process
I am currently working on biomass. I am trying to quantify how much the level of uncertainties in biomass estimations will affect the level of uncertainty in biomass fluxes.
For example, I know the ...
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89 views
How to incorporate prior knowledge in GPML?
I am using the MATLAB code for Rasmussen & Williams' book Gaussian Processes for Machine Learning.
How can one incorporate prior knowledge in Gaussian process regression? Say, that the variance ...
