Research - NAVER LABS Europe
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RESEARCH

Our technical expertise is enriched with a deep understanding of how people interact with technology.

Some of the big cross-disciplinary challenges we address:

Representation learning: turning all data entities (text, images, videos, web pages, emails, …) into semantically-rich representations to that can be efficiently processed, mined and related to each other.

Interactive learning: including the human in the learning loop to benefit from the complementary capabilities of humans and machines

Lifelong learning: exploring how to learn and manage prediction systems, policies or processes in a sustainable manner, i.e. in a manner that makes maximum reuse of previous experiences.

Machine reasoning: connecting existing pieces of knowledge to create new knowledge, e.g. being able to answer complex questions that require multiple supporting facts.

Decision making: learning how to make actionable decisions in uncertainty, especially in ever-changing environments

Agility: we live in an ever-changing world which means the technology we use must evolve in synergy with the people and business processes that touch it.

User centric: an important challenge in any technology is to the adoption by people. Only then does science become innovation. Our solutions are grounded in a deep understanding of how people work and how technology can help them every day.

blank The AI for Robotics theme comprises work from multiple research groups.

Collaboration

NAVER Labs Europe is a hub of NAVER’s global AI R&D Belt, a network of centres of excellence in Korea, Japan, Vietnam & Europe. By collaborating with different partners we aim to make AI technology in South East Asia and Europe more competitive.

Our scientists collaborate with national and international partners, academics and businesses to solve problems and invent technology and services that will have impact in the real world.

Discover how our research is recognized.

Research illustrating image woman and 2 man in front of computers
11 October 2020

From Abstract Specifications to Application Generation

9 September 2020

Transforming scholarship in the archives through handwritten text recognition

31 August 2020

Guided Exploration of User Groups

23 August 2020

2020 European Conference on Computer Vision (ECCV 2020)

23rd-28th August 2020, Glasgow, Scotland, UK. Tutorial accepted by Gabriela Csurka at al: "Domain Adaptation for Visual Applications"
20 July 2020

PRAIRIE and MIAI International Summer School 2020

PAISS HAS BEEN POSTPONED - new dates will be shared in May.
20th-24th JULY 2020. The third edition of this AI summer school will be held in Grenoble.
14 June 2020

Conference on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, Washington , USA

NAVER LABS Europe is co-organising the 3D Humans workshop.
28 May 2020

Fast Adaptation of Reinforcement-Learned Robot Navigation Skills to Human Preferences

Our navigation system enables robots to adapt to specific real-world environments and use cases with only small amounts of human preference data.
27 May 2020

A machine translation model for Covid-19 research

We're releasing a state-of-the-art multilingual and multi-domain neural machine translation model specialised for biomedical data that enables translation into English from five languages (French, German, Italian, Spanish and Korean).
28 April 2020

Vital Records and Deep Learning are helping us uncover the past from historical handwritten records

A new platform based on deep-learning approaches to handwritten-text recognition and information extraction enables data from century-old documents to be parsed and analysed, making it possible to explore epidemics and the evolution of populations over time.

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