Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Smoothness and Stability in GANs   Generative adversarial networks, or GANs, commonly display unstable behavior
during training. In this work, we develop a principled theoretical framework
for understanding the stability of various types of GANs. In particular, we
derive conditions that guarantee eventual stationarity of the generator when it
is trained with gradient descent, conditions that must be satisfied by the
divergence that is minimized by the GAN and the generator's architecture. We
find that existing GAN variants satisfy some, but not all, of these conditions.
Using tools from convex analysis, optimal transport, and reproducing kernels,
we construct a GAN that fulfills these conditions simultaneously. In the
process, we explain and clarify the need for various existing GAN stabilization
techniques, including Lipschitz constraints, gradient penalties, and smooth
activation functions.

32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
27
The categories of this paper are: comp-gas
2
The categories of this paper are: math
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
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The categories of this paper are: hep-lat
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The categories of this paper are: alg-geom
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The categories of this paper are: q-fin
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The categories of this paper are: eess
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex