Teknologiseminar

From Robin

(Difference between revisions)
Jump to: navigation, search
(Dates and subjects - Autumn 2021 – Thursdays 12:00-12:45)
(Dates and subjects - Autumn 2021 – Thursdays 12:00-12:45)
Line 36: Line 36:
|  18.11 ||  Title of presentation?? || Minh   
|  18.11 ||  Title of presentation?? || Minh   
|-  
|-  
-
|  25.11 ||  Title of presentation?? || Adel (remove this note to confirm)
+
|  25.11 ||  Title of presentation?? || free spot
|-  
|-  
| 02.12 ||  Casual lunch meeting ||  Bring your own lunch
| 02.12 ||  Casual lunch meeting ||  Bring your own lunch

Revision as of 16:03, 4 November 2021

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 - Autumn 2021 – Thursdays 12:00-12:45

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

When What Who
02.09 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 Title of presentation?? Yngve (remove this note to confirm)
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 Title of presentation?? Minh
25.11 Title of presentation?? free spot
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
Personal tools
Front page