Teknologiseminar
From Robin
(Difference between revisions)
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=== Examples of interesting topics for technology introduction === | === Examples of interesting topics for technology introduction === | ||
| + | Feel free to add topics to the wishlist! | ||
* Robotics | * Robotics | ||
| + | ** Reinforcement learning for robotics | ||
** SLAM | ** SLAM | ||
** embodied cognition | ** embodied cognition | ||
| - | ** | + | ** Swarm |
| - | + | ||
| - | * | + | * Neural networks |
| - | ** Recursive NNs | + | ** Recursive NNs and LSTMs |
| - | + | ||
| - | + | ||
** NEAT / HyperNEAT | ** NEAT / HyperNEAT | ||
** Deep NNs | ** Deep NNs | ||
| - | * Evolutionary algorithms | + | * Evolutionary algorithms and other types of optimization |
** Performance comparison of EAs (statistical tests) | ** Performance comparison of EAs (statistical tests) | ||
** Differential evolution | ** Differential evolution | ||
** Diversity preservation methods | ** Diversity preservation methods | ||
** Novelty search, MAP-Elites and variants | ** Novelty search, MAP-Elites and variants | ||
| + | ** Bayesian optimization | ||
* Tools | * Tools | ||
** R | ** R | ||
| + | ** Python as alternative to R, incl. matplotlib | ||
** ROS | ** ROS | ||
| - | ** Deep learning | + | ** Deep learning frameworks and practice |
Revision as of 10:12, 9 February 2018
Meeting structure
Place: ROBIN pause area, 4th floor Ole-Johan Dahls hus
11:30-11:45 Brief exchange of recent news, plans etc.
11:45-12:30 Technology / Own Research / Journal review (see guidelines), including discussion
Dates and subjects - Spring 2017 – Fridays 11:30-12:30 - Eat your own lunch while listening / discussing
DON'T EDIT THIS WITH THE RICH EDITOR! IT DESTROYS THE TEXT VERSION!
| When | Who | Content (title and type (tech/res/review) |
| 09.02 | Charles | Deep predictive models in interactive music (res) |
| 23.02 | - | (Winter vacation) |
| 09.03 | ||
| 23.03 | ||
| 06.04 | ||
| 20.04 | ||
| 04.05 | ||
| 18.05 | ||
| 01.06 | ||
| 15.06 | ||
| 29.06 |
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
- R
- Python as alternative to R, incl. matplotlib
- ROS
- Deep learning frameworks and practice
