Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Premise Selection for Theorem Proving by Deep Graph Embedding   We propose a deep learning-based approach to the problem of premise
selection: selecting mathematical statements relevant for proving a given
conjecture. We represent a higher-order logic formula as a graph that is
invariant to variable renaming but still fully preserves syntactic and semantic
information. We then embed the graph into a vector via a novel embedding method
that preserves the information of edge ordering. Our approach achieves
state-of-the-art results on the HolStep dataset, improving the classification
accuracy from 83% to 90.3%.

8
The categories of this paper are: hep-ex
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg