Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Autoregressive Models for Sequences of Graphs   This paper proposes an autoregressive (AR) model for sequences of graphs,
which generalises traditional AR models. A first novelty consists in
formalising the AR model for a very general family of graphs, characterised by
a variable topology, and attributes associated with nodes and edges. A graph
neural network (GNN) is also proposed to learn the AR function associated with
the graph-generating process (GGP), and subsequently predict the next graph in
a sequence. The proposed method is compared with four baselines on synthetic
GGPs, denoting a significantly better performance on all considered problems.

14
The categories of this paper are: math-ph
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
0
The categories of this paper are: hep-ph
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ