
Graph Neural Networks: A Review of Methods and Applications - painful
https://arxiv.org/abs/1812.08434
======
visarga
Graph network reviews seem all the rage, here's another recent one:

"A Comprehensive Survey on Graph Neural Networks "
[https://arxiv.org/abs/1901.00596](https://arxiv.org/abs/1901.00596)

~~~
karimtr
There is definitely a lot of interest around the topic. Over 20 graph related
papers where accepted for ICLR 2019 -
[https://openreview.net/group?id=ICLR.cc/2019/Conference](https://openreview.net/group?id=ICLR.cc/2019/Conference)

~~~
stochastic_monk
It’s worth stating that being able to work with hierarchical or graphical data
is powerful and has very broad applications. The interest is not purely
intellectual.

------
a_bonobo
Are there any good Python libraries that make working with Graph Neural
Networks as easy as working with Keras/Pytorch/fast.ai?

All I can find is
[https://github.com/tkipf/gcn](https://github.com/tkipf/gcn), and from the
same authors reimplementations in Pytorch
[https://github.com/tkipf/pygcn](https://github.com/tkipf/pygcn) and Keras:
[https://github.com/tkipf/keras-gcn](https://github.com/tkipf/keras-gcn) many
stars for the main repo (1100), but not that much usage?

~~~
logancg
Deep Graph Library (DGL) [1] came out in November and I've heard good things.
It looks easy and intuitive.

[1] [https://github.com/dmlc/dgl](https://github.com/dmlc/dgl)

------
kaivi
I'm just curious - why do I primarily see Chinese researchers publishing deep
learning stuff on arXiv? Is it subsidized over there? Just look at the
publications linked in this thread so far, 2/3 are from Beijing.

~~~
logancg
There are a lot of talented ML researchers in China. This is a product of (a)
the government and major companies (i.e. BAT) investing heavily in fundamental
ML research (b) the population size (c) a long tradition of STEM-focused
education in China. So, it's not surprising that would be the case.

The interesting questions are if China is uniquely focused on deep learning
over other ML techniques, and Chinese research compares in terms of quality.
Anecdotally (speaking as a researcher in the field) papers from Chinese
institutions seem disproportionately focused on deep learning (whereas, for
example, the UK does great work in Bayesian ML and the US does
disproprotionately well in NLP). I'm not a deep learning researcher so I can't
judge the technical merit, but I was just at NeurIPS in Montreal, and I saw
about equal representation of Chinese institutions as South Korean ones. South
Korea, with ~1/25 the population, punches way above its weight per capita.

~~~
taneq
I thought the question was more "why arXiv and not other journals" in which
case maybe 'prestigious' Western journal publications just aren't valued as
much in China?

~~~
nl
Almost all ML research is published on arXiv.

In ML (as in most of Comp Sci) conference proceedings (NeurIPS, ICML etc) are
where the prestige publishing is.

