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Graph neural networks in node classification: survey and evaluation
Neural networks have been proved efficient in improving many machine learning tasks such
as convolutional neural networks and recurrent neural networks for computer vision and …
as convolutional neural networks and recurrent neural networks for computer vision and …
Neural machine translation: A review
F Stahlberg - Journal of Artificial Intelligence Research, 2020 - jair.org
The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …
natural language into another, has experienced a major paradigm shift in recent years …
Improving massively multilingual neural machine translation and zero-shot translation
Massively multilingual models for neural machine translation (NMT) are theoretically
attractive, but often underperform bilingual models and deliver poor zero-shot translations. In …
attractive, but often underperform bilingual models and deliver poor zero-shot translations. In …
Survey of low-resource machine translation
We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …
research. There are currently around 7,000 languages spoken in the world and almost all …
Dynamical variational autoencoders: A comprehensive review
Variational autoencoders (VAEs) are powerful deep generative models widely used to
represent high-dimensional complex data through a low-dimensional latent space learned …
represent high-dimensional complex data through a low-dimensional latent space learned …
Identifying and controlling important neurons in neural machine translation
Neural machine translation (NMT) models learn representations containing substantial
linguistic information. However, it is not clear if such information is fully distributed or if some …
linguistic information. However, it is not clear if such information is fully distributed or if some …
Learning language specific sub-network for multilingual machine translation
Multilingual neural machine translation aims at learning a single translation model for
multiple languages. These jointly trained models often suffer from performance degradation …
multiple languages. These jointly trained models often suffer from performance degradation …
Latent alignment and variational attention
Neural attention has become central to many state-of-the-art models in natural language
processing and related domains. Attention networks are an easy-to-train and effective …
processing and related domains. Attention networks are an easy-to-train and effective …
GeoTrackNet—A Maritime Anomaly Detector Using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection
D Nguyen, R Vadaine, G Hajduch… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Representing maritime traffic patterns and detecting anomalies from them are key to vessel
monitoring and maritime situational awareness. We propose a novel approach—referred to …
monitoring and maritime situational awareness. We propose a novel approach—referred to …
Dynamic context-guided capsule network for multimodal machine translation
Multimodal machine translation (MMT), which mainly focuses on enhancing text-only
translation with visual features, has attracted considerable attention from both computer …
translation with visual features, has attracted considerable attention from both computer …