Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural Painters: A learned differentiable constraint for generating
  brushstroke paintings   We explore neural painters, a generative model for brushstrokes learned from
a real non-differentiable and non-deterministic painting program. We show that
when training an agent to "paint" images using brushstrokes, using a
differentiable neural painter leads to much faster convergence. We propose a
method for encouraging this agent to follow human-like strokes when
reconstructing digits. We also explore the use of a neural painter as a
differentiable image parameterization. By directly optimizing brushstrokes to
activate neurons in a pre-trained convolutional network, we can directly
visualize ImageNet categories and generate "ideal" paintings of each class.
Finally, we present a new concept called intrinsic style transfer. By
minimizing only the content loss from neural style transfer, we allow the
artistic medium, in this case, brushstrokes, to naturally dictate the resulting
style.

30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
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The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
11
The categories of this paper are: hep-lat