Published July 18, 2019
| Version v1
Conference paper
Open
Can Neural Networks Learn Symbolic Rewriting?
- 1. University of Warsaw, Poland
- 2. Czech Technical University in Prague
- 3. University of Innsbruck
Description
This work investigates if the current neural architectures are adequate for learning symbolic rewriting. Two kinds of data sets are proposed for this research – one based on automated proofs and the other being a synthetic set of polynomial terms. The experiments with use of the current neural machine translation models are performed and its results are discussed. Ideas for extending this line of research are proposed and its relevance is motivated.
Files
40.pdf
Files
(144.5 kB)
Name | Size | Download all |
---|---|---|
md5:9e1de3839cfb3618ec079ee2e24ff795
|
144.5 kB | Preview Download |