Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Geometric Sample Reweighting for Monte Carlo Integration   We present a general sample reweighting scheme and its underlying theory for
the integration of an unknown function with low dimensionality. Our method
produces better results than standard weighting schemes for common sampling
strategies, while avoiding bias. Our main insight is to link the weight
derivation to the function reconstruction process during integration. The
implementation of our solution is simple and results in an improved convergence
behavior. We illustrate its benefit by applying our method to multiple Monte
Carlo rendering problems.

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The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
32
The categories of this paper are: atom-ph
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The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
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The categories of this paper are: eess
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The categories of this paper are: bayes-an
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The categories of this paper are: acc-phys
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The categories of this paper are: chem-ph
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The categories of this paper are: gr-qc
3
The categories of this paper are: physics