Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Variational Recurrent Neural Networks for Graph Classification   We address the problem of graph classification based only on structural
information. Inspired by natural language processing techniques (NLP), our
model sequentially embeds information to estimate class membership
probabilities. Besides, we experiment with NLP-like variational regularization
techniques, making the model predict the next node in the sequence as it reads
it. We experimentally show that our model achieves state-of-the-art
classification results on several standard molecular datasets. Finally, we
perform a qualitative analysis and give some insights on whether the node
prediction helps the model better classify graphs.

30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th