Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: N-Gram Graph: Simple Unsupervised Representation for Graphs, with
  Applications to Molecules   Machine learning techniques have recently been adopted in various
applications in medicine, biology, chemistry, and material engineering. An
important task is to predict the properties of molecules, which serves as the
main subroutine in many downstream applications such as virtual screening and
drug design. Despite the increasing interest, the key challenge is to construct
proper representations of molecules for learning algorithms. This paper
introduces the N-gram graph, a simple unsupervised representation for
molecules. The method first embeds the vertices in the molecule graph. It then
constructs a compact representation for the graph by assembling the vertex
embeddings in short walks in the graph, which we show is equivalent to a simple
graph neural network that needs no training. The representations can thus be
efficiently computed and then used with supervised learning methods for
prediction. Experiments on 60 tasks from 10 benchmark datasets demonstrate its
advantages over both popular graph neural networks and traditional
representation methods. This is complemented by theoretical analysis showing
its strong representation and prediction power.

7
The categories of this paper are: hep-th
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
25
The categories of this paper are: patt-sol
17
The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
28
The categories of this paper are: alg-geom
2
The categories of this paper are: math