A survey of deep learning techniques for neural machine translation
In recent years, natural language processing (NLP) has got great development with deep
learning techniques. In the sub-field of machine translation, a new approach named Neural …
learning techniques. In the sub-field of machine translation, a new approach named Neural …
[PDF][PDF] Deep Neural Networks in Machine Translation: An Overview.
MT aims to find for the source language sentence the most probable target language
sentence that shares the most similar meaning. Essentially, MT is a sequence-to-sequence …
sentence that shares the most similar meaning. Essentially, MT is a sequence-to-sequence …
Task-oriented multi-user semantic communications
While semantic communications have shown the potential in the case of single-modal single-
users, its applications to the multi-user scenario remain limited. In this paper, we investigate …
users, its applications to the multi-user scenario remain limited. In this paper, we investigate …
Deep learning enabled semantic communication systems
Recently, deep learned enabled end-to-end communication systems have been developed
to merge all physical layer blocks in the traditional communication systems, which make joint …
to merge all physical layer blocks in the traditional communication systems, which make joint …
Convolutional sequence to sequence learning
The prevalent approach to sequence to sequence learning maps an input sequence to a
variable length output sequence via recurrent neural networks. We introduce an architecture …
variable length output sequence via recurrent neural networks. We introduce an architecture …
Tensor2tensor for neural machine translation
arxiv:1803.07416v1 [cs.LG] 16 Mar 2018 Page 1 Tensor2Tensor for Neural Machine Translation
Ashish Vaswani1, Samy Bengio1, Eugene Brevdo1, Francois Chollet1, Aidan N. Gomez1 …
Ashish Vaswani1, Samy Bengio1, Eugene Brevdo1, Francois Chollet1, Aidan N. Gomez1 …
Tienet: Text-image embedding network for common thorax disease classification and reporting in chest x-rays
Chest X-rays are one of the most common radiological examinations in daily clinical
routines. Reporting thorax diseases using chest X-rays is often an entry-level task for …
routines. Reporting thorax diseases using chest X-rays is often an entry-level task for …
A convolutional encoder model for neural machine translation
The prevalent approach to neural machine translation relies on bi-directional LSTMs to
encode the source sentence. In this paper we present a faster and simpler architecture …
encode the source sentence. In this paper we present a faster and simpler architecture …
[PDF][PDF] Relation classification via multi-level attention cnns
Relation classification is a crucial ingredient in numerous information extraction systems
seeking to mine structured facts from text. We propose a novel convolutional neural network …
seeking to mine structured facts from text. We propose a novel convolutional neural network …
[معلومات الإصدار][C] Neural machine translation
P Koehn - 2020 - books.google.com
Deep learning is revolutionizing how machine translation systems are built today. This book
introduces the challenge of machine translation and evaluation-including historical …
introduces the challenge of machine translation and evaluation-including historical …