Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: BEGAN: Boundary Equilibrium Generative Adversarial Networks   We propose a new equilibrium enforcing method paired with a loss derived from
the Wasserstein distance for training auto-encoder based Generative Adversarial
Networks. This method balances the generator and discriminator during training.
Additionally, it provides a new approximate convergence measure, fast and
stable training and high visual quality. We also derive a way of controlling
the trade-off between image diversity and visual quality. We focus on the image
generation task, setting a new milestone in visual quality, even at higher
resolutions. This is achieved while using a relatively simple model
architecture and a standard training procedure.

13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex