Teknologiseminar
From Robin
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| 18.02 || Casual meeting || └[∵┌]└[ ∵ ]┘[┐∵]┘ | | 18.02 || Casual meeting || └[∵┌]└[ ∵ ]┘[┐∵]┘ | ||
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- | | 25.02 || | + | | 25.02 || Do your dance moves seem too robotic? You might be one of Benedikte's trained networks. || Benedikte |
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| 04.03 || || | | 04.03 || || |
Revision as of 14:59, 16 January 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 - Spring 2021 – Thursdays 12:00-12:45
5-20 min housekeeping/updates + 15 min talk (casual meetings = round-table)
When | What | Who |
21.01 | Who is Diana? What will she do here? | Diana |
28.01 | Casual meeting | └[∵┌]└[ ∵ ]┘[┐∵]┘ |
04.02 | ||
11.02 | ||
18.02 | Casual meeting | └[∵┌]└[ ∵ ]┘[┐∵]┘ |
25.02 | Do your dance moves seem too robotic? You might be one of Benedikte's trained networks. | Benedikte |
04.03 | ||
11.03 | Casual meeting | └[∵┌]└[ ∵ ]┘[┐∵]┘ |
18.03 | ||
25.03 | ||
01.04 | Easter holiday | └[∵┌]└[ ∵ ]┘[┐∵]┘ |
08.04 | ||
15.04 | ||
22.04 | Casual meeting | └[∵┌]└[ ∵ ]┘[┐∵]┘ |
29.04 | ||
06.05 | ||
13.05 | National holiday | └[∵┌]└[ ∵ ]┘[┐∵]┘ |
20.05 | ||
27.05 | ||
03.06 | Casual meeting | └[∵┌]└[ ∵ ]┘[┐∵]┘ |
10.06 | ||
17.06 | ||
24.06 | Casual meeting | └[∵┌]└[ ∵ ]┘[┐∵]┘ |
To be continued | in August |
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