Teknologiseminar

Fra Robin

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(Dates and subjects - Spring 2022 – Thursdays 12:00-12:45)
Linje 24: Linje 24:
|  03.03 || Alex || Neural oscillator models
|  03.03 || Alex || Neural oscillator models
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|  10.03 || ||  
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|  10.03 || Stefano Nichele (OsloMet) || Neural Cellular Automata (and other topics)
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|  17.03 || No presentation/Casual meeting ||  
|  17.03 || No presentation/Casual meeting ||  

Versjonen fra 16. feb 2022 kl. 09:38

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
27.01 Introductions, news
03.02 Computational resources (Slides) @Vegard
10.02 General update (Annual PhD report 2021)
17.02 Kai Catastrophic Forgetting
24.02 No presentation/Casual meeting
03.03 Alex Neural oscillator models
10.03 Stefano Nichele (OsloMet) Neural Cellular Automata (and other topics)
17.03 No presentation/Casual meeting
24.03 Emma
31.03 No presentation/Casual meeting
07.04 Ulysse? Adherence forecasting for G-ICBT
14.04 Easter break – no meeting
21.04
28.04 Adel
05.05
12.05 No presentation/Casual meeting
19.05 Diana
26.05 (Yngve)


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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