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The Cartographer
Deep Probabilistic Programming Languages: A Qualitative Study
April 17, 2018 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Guillaume Baudart, Martin Hirzel, Louis Mandel
arXiv ID
1804.06458
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.PL
Citations
11
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Deep probabilistic programming languages try to combine the advantages of deep learning with those of probabilistic programming languages. If successful, this would be a big step forward in machine learning and programming languages. Unfortunately, as of now, this new crop of languages is hard to use and understand. This paper addresses this problem directly by explaining deep probabilistic programming languages and indirectly by characterizing their current strengths and weaknesses.
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