Neural Monkey: An Open-source Tool for Sequence Learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10372014" target="_blank" >RIV/00216208:11320/17:10372014 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1515/pralin-2017-0001" target="_blank" >http://dx.doi.org/10.1515/pralin-2017-0001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1515/pralin-2017-0001" target="_blank" >10.1515/pralin-2017-0001</a>
Alternative languages
Result language
angličtina
Original language name
Neural Monkey: An Open-source Tool for Sequence Learning
Original language description
In this paper, we announce development of Neural Monkey - an open-source neural machine translation (NMT) and general sequence-to-sequence learning system built over TensorFlow machine learning library. The system provides a high-level API with support for fast prototyping of complex architectures with multiple sequence encoders and decoders. These models' overall architecture is specified in easy-to-read configuration files. The long-term goal of Neural Monkey project is to create and maintain a growing collection of implementations of recently proposed components or methods, and therefore it is designed to be easily extensible. The trained models can be deployed either for batch data processing or as a web service. In the presented paper, we describe the design of the system and introduce the reader to running experiments using Neural Monkey.
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
The Prague Bulletin of Mathematical Linguistics
ISSN
0032-6585
e-ISSN
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Volume of the periodical
Neuveden
Issue of the periodical within the volume
107
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
13
Pages from-to
5-17
UT code for WoS article
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EID of the result in the Scopus database
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