DeepLearn 2022 Spring
5th International School
on Deep Learning
Guimarães, Portugal · April 18-22, 2022
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  • Call DeepLearn 2022 Spring
  • Poster DeepLearn 2022 Spring
  • Lecture Materials
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  • Accommodation
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    • Sponsors
    • Code of conduct
    • Visa
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  • Home
  • Schedule
  • Lecturers
  • Travel
  • Accommodation
  • Info
    • Sponsors
    • Code of conduct
    • Visa
    • News

UPDATE
ON ADVANCES
IN DEEP LEARNING

MORE INFO

LISTEN TO
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ACADEMICS
& INDUSTRY PIONEERS

SPEAKERS

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UPDATED
ON DEEP LEARNING

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On-site registration

SCOPE

DeepLearn 2022 Spring will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning.

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ADDRESSED TO

Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well.

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VENUE

DeepLearn 2022 Spring will take place in Guimarães, in the north of Portugal, listed as UNESCO World Heritage Site and often referred to as the birthplace of the country.

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STRUCTURE

  • 3 courses will run in parallel during the whole event.
  • Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.

Full in vivo online participation will be possible. However, the organizers highlight the importance of face to face interaction and networking in this kind of research training event.

Special Sessions

OPEN SESSION

An open session will collect 5-minute voluntary presentations of work in progress by participants.

They should submit a half-page abstract containing the title, authors, and summary of the research to david@irdta.eu by April 10, 2022.

INDUSTRIAL SESSION

A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed.

People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david@irdta.eu by April 10, 2022.

EMPLOYER SESSION

Firms searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts.

It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event.

People in charge of the search must register for the event. Expressions of interest have to be submitted to david@irdta.eu by April 10, 2022.

ORGANIZING COMMITTEE

  • Dalila Durães (Braga, co-chair)
  • José Machado (Braga, co-chair)
  • Carlos Martín-Vide (Tarragona, program chair)
  • Sara Morales (Brussels)
  • Paulo Novais (Braga, co-chair)
  • David Silva (London, co-chair)

QUESTIONS AND FURTHER INFORMATION

  • Mail to: david@irdta.eu
  • A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.

Sponsors

DeepLearn 2022 Spring

CO-ORGANIZERS

Algoritmi Center, University of Minho, Guimarães

School of Engineering, University of Minho

Intelligent Systems Associate Laboratory, University of Minho

Rovira i Virgili University

Municipality of Guimarães

Institute for Research Development, Training and Advice – IRDTA, Brussels/London

Active links
  • DeepLearn 2022 Autumn – 7th International School on Deep Learning
  • DeepLearn 2022 Summer – 6th International School on Deep Learning
  • TPNC 2020 & 2021 – 9th-10th International Conference on the Theory and Practice of Natural Computing
  • SLSP 2020 & 2021 – 8th-9th International Conference on Statistical Language and Speech Processing
  • AlCoB 2020 & 2021 – 7th-8th International Conference on Algorithms for Computational Biology
  • LATA 2020 & 2021 – 14th-15th International Conference on Language and Automata Theory and Applications
Past links
  • DeepLearn 2021 Summer
  • DeepLearn 2019
  • DeepLearn 2018
  • DeepLearn 2017
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