Teknologiseminar

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(Dates and subjects - Autumn 2021 – Thursdays 12:00-12:45)
(Dates and subjects - Autumn 2021 – Thursdays 12:00-12:45)
Linje 32: Linje 32:
|'''When''' || '''What'''||  '''Who'''   
|'''When''' || '''What'''||  '''Who'''   
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|  02.09 || Introductions, news ||  
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|  02.01 || Introductions, news ||  
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|  09.09 || (tour de RITMO day) ||  
|  09.09 || (tour de RITMO day) ||  

Versjonen fra 11. jan 2022 kl. 10:44

Innhold

Meeting structure

Place: ROBIN pause area, 4th floor Ole-Johan Dahls hus / gather town

12:00-12:15 Brief exchange of recent news, plans, updates, etc.

~12:20-12:35 Presentation on: Technology / Own Research / Journal review (see guidelines), time excludes discussion

Dates and subjects - Spring 2022 – Thursdays 12:00-12:45

5-20 min housekeeping/updates + 15 min talk

When What Who
20.01 Introductions, news
27.01 Vegard Computational resources
03.02
10.02
17.02
24.02

Dates and subjects - Autumn 2021 – Thursdays 12:00-12:45

5-20 min housekeeping/updates + 15 min talk (casual meetings = round-table)

When What Who
02.01 Introductions, news
09.09 (tour de RITMO day)
16.09 Casual lunch meeting Bring your own lunch
23.09 Title of presentation?? Marieke
30.09 Casual lunch meeting Bring your own lunch
07.10 Title of presentation?? Mojtaba
14.10 --- ---
21.10 Casual lunch meeting Bring your own lunch
28.10 Offline Reinforcement Learning Ulysse
04.11 Unity Machine Learning Agents for Evolutionary Robotics Frank
11.11 Casual lunch meeting Bring your own lunch
18.11 Emotion and mood recognition with speech Minh
25.11 Design, Kinematic Modeling, and Validation of a Robotic-Assisted Transesophageal Echocardiography System Reza
02.12 Casual lunch meeting Bring your own lunch
09.12 Title of presentation?? Kyrre
16.12 Title of presentation?? Katrine (remove this note to confirm)
To be continued in January (remove this note to confirm)

Overview of earlier seminars

Examples of interesting topics for technology introduction

Feel free to add topics to the wishlist!

  • Robotics
    • Reinforcement learning for robotics
    • SLAM
    • embodied cognition
    • Swarm
  • Neural networks
    • Recursive NNs and LSTMs
    • NEAT / HyperNEAT
    • Deep NNs
  • Evolutionary algorithms and other types of optimization
    • Performance comparison of EAs (statistical tests)
    • Differential evolution
    • Diversity preservation methods
    • Novelty search, MAP-Elites and variants
    • Bayesian optimization
  • Tools
    • SLURM
    • R
    • Python as alternative to R, incl. matplotlib
    • ROS
    • Deep learning frameworks and practice
    • Unity ML agents
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