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Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Since its introduction, it has been one of the mostExpand
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Nematus: a Toolkit for Neural Machine Translation
We present Nematus, a toolkit for Neural Machine Translation. The toolkit prioritizes high translation accuracy, usability, and extensibility. Nematus has been used to build top-performingExpand
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Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism
We propose multi-way, multilingual neural machine translation. The proposed approach enables a single neural translation model to translate between multiple languages, with a number of parametersExpand
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On Using Monolingual Corpora in Neural Machine Translation
Recent work on end-to-end neural network-based architectures for machine translation has shown promising results for En-Fr and En-De translation. Arguably, one of the major factors behind thisExpand
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Zero-Resource Translation with Multi-Lingual Neural Machine Translation
In this paper, we propose a novel finetuning algorithm for the recently introduced multi-way, mulitlingual neural machine translate that enables zero-resource machine translation. When used togetherExpand
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Does Neural Machine Translation Benefit from Larger Context?
We propose a neural machine translation architecture that models the surrounding text in addition to the source sentence. These models lead to better performance, both in terms of general translationExpand
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The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation
The past year has witnessed rapid advances in sequence-to-sequence (seq2seq) modeling for Machine Translation (MT). The classic RNN-based approaches to MT were first out-performed by theExpand
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Montreal Neural Machine Translation Systems for WMT'15
Neural machine translation (NMT) systems have recently achieved results comparable to the state of the art on a few translation tasks, including English→French and English→German. The main purpose ofExpand
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Training Deeper Neural Machine Translation Models with Transparent Attention
While current state-of-the-art NMT models, such as RNN seq2seq and Transformers, possess a large number of parameters, they are still shallow in comparison to convolutional models used for both textExpand
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Revisiting Character-Based Neural Machine Translation with Capacity and Compression
Translating characters instead of words or word-fragments has the potential to simplify the processing pipeline for neural machine translation (NMT), and improve results by eliminatingExpand
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