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Is this a bug? Should we change the default distance for the Matern kernels?
For example, the following:
import numpy as np from tinygp import GaussianProcess, kernels random = np.random.default_rng(48392) X = random.uniform(-1, 1, (100, 2)) kernel = kernels.Matern32() print(GaussianProcess(kernel, X, diag=0.01).solver.normalization())
returns NaN, but replacing the kernel with:
kernel = kernels.Matern32(distance=kernels.L2Distance())
works…
See also #115
The text was updated successfully, but these errors were encountered:
dfm
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Is this a bug? Should we change the default distance for the Matern kernels?
For example, the following:
returns NaN, but replacing the kernel with:
works…
See also #115
The text was updated successfully, but these errors were encountered: