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Questions tagged [gpy]

Questions about GPy. GPy is a Gaussian Process (GP) framework written in Python. It includes support for basic GP regression, multiple output GPs (using coregionalization), various noise models, sparse GPs, non-parametric regression and latent variables. Use with the [python] tag

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how can we get multi-dimensional output from Gpy

I'm using Gpy to train a gaussian process regression model. The dimension for the input data is 4, the corresponding outputs' dimension shall be 3. I tried to just build one model for the outputs, and the model doesn't work at all. I tried to build…
smilingfish
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Python stats module: How to extract confidence/prediction intervals from GPy?

After having looked through all the docs and examples online, I have not been able to find a way to extract information regarding the confidence or prediction intervals from GPy models. I generate dummy data like this, ## Generating data for…
Coolio2654
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Python GPy module: how to plot model predictions over simple x-axis?

In Python, I was attempting to dive into the GPy library for estimating Gaussian Process models, when I encountered a stumbling block early on with simple plotting. For my data, I generated a simple sine wave with a squared growth rate added in…
Coolio2654
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Save and load kernel in GPy in a sparse gaussian process regression

I built and optimized a Sparse Gaussian Process Regression model using the GPy library. The documentation recommends to save the model as follow: To save a model it is best to save the m.param_array of it to disk (using numpy’s np.save).…
nbeuchat
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What is the difference between GPy.models.MultioutputGP and GPy.models.GPCoregioanlizedRegression?

The GPy library given examples on multioutput GP given here. There also exists another example within the GPy.examples.Regression module here. """ compares GPCoregionalizedRegression with MultioutputGP """ import matplotlib.pyplot as plt import…
theprogressor
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Change color from plot with GPy package

I made a plot by combining the GPY and matplotlib packages. However, for some reason I can not change the color of the line and the confidence interval, see code below. I changed the color of the plot to red, but nothing happens. In the package…
Berendvv
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The Covariance Matrix is not positive definite, even with jitter using GPy package in Python

I'm trying to find the optimal variance and lengthscale of a 2D model using Gaussian Process (by using the GPy package in Python). I already found the code to do just that, you can see it below: # sample inputs and outputs from 2d model X2 =…
Chroma 09
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How to get info of memory shared to GPU with Python (Windows)

I tried with nvidia_smi but only dedicated GPU memory could be retrieved. enter image description here As the task manager show, there is memory shared to GPU on windows, so how can I get this information with Python?
Dayong Chen
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Gaussian process GPy kernel input dimension

In GPy GPy.kern.kern(input_dim), the input dimension represents the dimensions of the input so that the kernel dimension matches the input dimension. "input_dim: is the number of dimensions to work on. Make sure to give the tight dimensionality of…
sree
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What is the meaning of the explanations and tables in the Gaussian process regression model in Python GPy?

To build the model, I input x,y,kernel and got the model m = GPy.models.GPRegression(x, y, kernel) then I did print(m) And got the description of model and following table Model: GP regression Objective: 2077.2427462362075 Number of…
stackman
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How to add constant Variance to the Matern Kernel in Gpytorch?

Previously I would have added the a WhiteNoiseKernel with the variance I wish. GPy kernels have a variance argument. How do I set the variance equivalently in gpytorch? Thanks to anyone who can point me to the right resource and solution.
Olli
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Strange Behavior in Emukit When Combining Multifidelity and Experimental Design

I have a Python code that aims to build several multi-fidelity models (one for each of several variables) and use Emukit's experimental design functions to update them iteratively. I am using simple uncertainty acquisition (ModelVariance) and the…
lwlzr
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How do I set the pso objective function to the estimated distribution function obtained from Gaussian process regression?

I am trying to create an estimated distribution function from the data in data.dat using Gaussian process regression and set it as the objective function of pso.but I keep getting the error below. I would like to create a function that returns LD…
stackman
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GPflow - GP classification with 1-dim Linear kernel fits poorly for 2 dimension data

Following the issue #1435, I have an additional question to how to use GPflow. I replicate the issue in an additional kernel: https://github.com/avalonhse/BayesNotebook/blob/master/Issue_2_GPFlow_Linear_Classification.ipynb My purpose is fitting an…
Hoang Le
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GPy and GPflow mathematical background - references

Does GPy and GPflow share a common mathematical background? I'm asking this because I'm using GPy but I cannot see the references. However, GPflow provides references in its examples. Is it Ok using keep using GPy or would you suggest the use GPflow…
Nip
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