Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Machine Learning Inversion Scheme for Determining Interaction from
  Scattering   We outline a machine learning strategy for determining the effective
interaction in the condensed phases of matter using scattering. Via a case
study of colloidal suspensions, we showed that the effective potential can be
probabilistically inferred from the scattering spectra without any restriction
imposed by model assumptions. Comparisons to existing parametric approaches
demonstrate the superior performance of this method in accuracy, efficiency,
and applicability. This method can effectively enable quantification of
interaction in highly correlated systems using scattering and diffraction
experiments.

10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
25
The categories of this paper are: patt-sol