# Luo 2019: Neural Decipherment via Minimum-Cost Flow: From Ugaritic to Linear B

> Jiaming Luo, Yuan Cao, Regina Barzilay, 2019. 5 records on Mysteries Department cite it. The cryptanalysis survey proposes its one-to-one min-cost-flow…

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[Sources](https://mysteriesdept.com/sources)[Voynich Manuscript](https://mysteriesdept.com/mysteries/voynich-manuscript)Luo 2019

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# Neural Decipherment via Minimum-Cost Flow: From Ugaritic to Linear B

Jiaming Luo, Yuan Cao, Regina Barzilay, 2019. _Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics_.

A neural model for deciphering lost languages, guided by patterns of historical sound change and trained by casting cognate matching as a minimum-cost flow problem; tested on Ugaritic and Linear B.

**Voynich Manuscript** Articledoi: **[10.18653/v1/p19-1303](https://doi.org/10.18653/v1/p19-1303)** Checked against the original0

## What it's used for here

The cryptanalysis survey proposes its one-to-one min-cost-flow constraint for aligning frequent Voynich tokens with a Latin lexicon; four other surveys also cite it.

## Cited by on this site 5 records

[5 methods surveys]

Signal processing, cryptanalysis, mathematics, frameworks of inquiry, inductive methods

SRC

## Cite it

```
Luo, J., Cao, Y., & Barzilay, R. (2019). Neural Decipherment via Minimum-Cost Flow: From Ugaritic to Linear B. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. https://doi.org/10.18653/v1/p19-1303
```

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