Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Controlling extrapolations of nuclear properties with feature selection   Predictions of nuclear properties far from measured data are inherently
imprecise because of uncertainties in our knowledge of nuclear forces and in
our treatment of quantum many-body effects in strongly-interacting systems.
While the model bias can be directly calculated when experimental data is
available, only an estimate can be made in the absence of such measurements.
Current approaches to compute the estimated bias quickly lose predictive power
when input variables such as proton or neutron number are extrapolated,
resulting in uncontrolled uncertainties in applications such as nucleosynthesis
simulations. In this letter, we present a novel technique to identify the input
variables of machine learning algorithms that can provide robust estimates of
model bias. Our process is based on selecting input variables, or features,
based on their probability distribution functions across the entire nuclear
chart. We illustrate our approach on the problem of quantifying the model bias
in nuclear binding energies calculated with Density Functional Theory (DFT). We
show that feature selection can systematically improve theoretical predictions
without increasing uncertainties.

10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
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The categories of this paper are: nlin
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The categories of this paper are: comp-gas
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The categories of this paper are: alg-geom
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The categories of this paper are: hep-lat