Neural machine translation

Applied sciences
Information engineering
Traitement automatique du l...
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Publications associées (31)

Subword Mapping and Anchoring across Languages

Andrei Popescu-Belis

State-of-the-art multilingual systems rely on shared vocabularies that sufficiently cover all considered languages. To this end, a simple and frequently used approach makes use of subword vocabularies constructed jointly over several languages. We hypothes ...

Assoc Computational Linguistics-Acl2021

System for planning and/or providing neuromodulation

Grégoire Courtine, Vincent Delattre, Marco Capogrosso, Fabien Bertrand Paul Wagner, Karen Minassian

The present invention relates to systems and methods for planning and/or providing neuromodulation One example system includesa stimulation related basic data storage module for storing stimulation related basic data,a stimulation related response data sto ...

2021

Discourse Phenomena in Machine Translation

Lesly Sadiht Miculicich Werlen

Machine Translation (MT) has made considerable progress in the past two decades, particularly after the introduction of neural network models (NMT). During this time, the research community has mostly focused on modeling and evaluating MT systems at the se ...

EPFL2021

Content-Preserving Unpaired Translation from Simulated to Realistic Ultrasound Images

Devavrat Tomar, Lin Zhang

Interactive simulation of ultrasound imaging greatly facilitates sonography training. Although ray-tracing based methods have shown promising results, obtaining realistic images requires substantial modeling effort and manual parameter tuning. In addition, ...

Springer2021

Pose Transformers (POTR): Human Motion Prediction with Non-Autoregressive Transformers

Jean-Marc Odobez, Michael Villamizar

We propose to leverage Transformer architectures for non-autoregressive human motion prediction. Our approach decodes elements in parallel from a query sequence, instead of conditioning on previous predictions such as in state-of-the-art RNN-based approach ...

IEEE COMPUTER SOC2021

Epidemic mitigation by statistical inference from contact tracing data

Florent Gérard Krzakala, Lenka Zdeborová, Maria Refinetti, Indaco Biazzo, Giovanni Catania

Contact tracing is an essential tool to mitigate the impact of a pandemic, such as the COVID-19 pandemic. In order to achieve efficient and scalable contact tracing in real time, digital devices can play an important role. While a lot of attention has been ...

National Academy of Sciences2021

Loss landscape and symmetries in Neural Networks

Mario Geiger

Neural networks (NNs) have been very successful in a variety of tasks ranging from machine translation to image classification. Despite their success, the reasons for their performance are still not well-understood. This thesis explores two main themes: lo ...

EPFL2021

Learning-based Image Coding: Early Solutions Reviewing and Subjective Quality Evaluation

Touradj Ebrahimi, Pinar Akyazi

Nowadays, image and video are the data types that consume most of the resources of modern communication channels, both in fixed and wireless networks. Thus, it is vital to compress visual data as much as possible, while maintaining some target quality leve ...

SPIE-INT SOC OPTICAL ENGINEERING2021

Bioelectronic medicine for the autonomic nervous system: clinical applications and perspectives

Silvestro Micera, Ivo Strauss

Bioelectronic medicine (BM) is an emerging new approach for developing novel neuromodulation therapies for pathologies that have been previously treated with pharmacological approaches. In this review, we will focus on the neuromodulation of autonomic nerv ...

IOP PUBLISHING LTD2021

Visual Focus of Attention Estimation in 3D Scene with an Arbitrary Number of Targets

Jean-Marc Odobez, Rémy Alain Siegfried

Visual Focus of Attention (VFOA) estimation in conversation is challenging as it relies on difficult to estimate information (gaze) combined with scene features like target positions and other contextual information (speaking status) allowing to disambigua ...

IEEE COMPUTER SOC2021

Robust Learning-Augmented Caching: An Experimental Study

Adam Teodor Polak

Effective caching is crucial for performance of modern-day computing systems. A key optimization problem arising in caching – which item to evict to make room for a new item – cannot be optimally solved without knowing the future. There are many classical ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

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