Teknologiseminar

Fra Robin

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(Dates and subjects - Spring 2022 – Thursdays 12:00-12:45)
(Dates and subjects - Spring 2022 – Thursdays 12:00-12:45)
Linje 45: Linje 45:
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|  19.05 || Tobias Mahler (jus) om VIROS ||  
|  19.05 || Tobias Mahler (jus) om VIROS ||  
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|  26.05 || (Yngve) ||
 
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|  26.05 || Presentation of Simula/UiO's [https://www.mn.uio.no/fysikk/english/research/projects/bio-inspired-neural-networks-for-ai-applications/index.html BioAI research group] || [https://www.simula.no/people/mikkel Mikkel Lepperød]||  
|  26.05 || Presentation of Simula/UiO's [https://www.mn.uio.no/fysikk/english/research/projects/bio-inspired-neural-networks-for-ai-applications/index.html BioAI research group] || [https://www.simula.no/people/mikkel Mikkel Lepperød]||  

Versjonen fra 9. mai 2022 kl. 12:10

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 Diana Overview on the VIROS project [1]
28.04 Adel
05.05 Mats (Cancelled, no presentation) Cancelled
12.05 No presentation/Casual meeting
19.05 Tobias Mahler (jus) om VIROS
26.05 Presentation of Simula/UiO's BioAI research group Mikkel Lepperød


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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