Progress for week 43 (2018)
From Robin
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* Autoencoder implemented. Currently training models based on this architecture | * Autoencoder implemented. Currently training models based on this architecture | ||
* Thesis worked on | * Thesis worked on | ||
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+ | == Anders Rønningstad == | ||
+ | === Budget === | ||
+ | * Finish own implementation of semi Mathematical. | ||
+ | * Find out more on how to implement real mathematical optimization | ||
+ | * Run simulations | ||
+ | ** compare results | ||
+ | |||
+ | === Accounting === | ||
+ | * Found a way to implement mathematical (with asumption) | ||
+ | * Ran some simulations |
Current revision as of 11:00, 26 October 2018
Contents |
David Kolden
Budget
- Finish essay
- Implement working camera node
Accounting
- 85% finished with essay
Jonas Waaler
Budget
- Implement peak detector to clean up training data
- Test CoordConv prinsip
- Implement autoencoder - transfer weights and create regressor
- Evaluate trained models
Accounting
- Peak detector algorithm implemented
- CoordConv tested
- Not making any difference
- Autoencoder implemented. Currently training models based on this architecture
- Thesis worked on
Anders Rønningstad
Budget
- Finish own implementation of semi Mathematical.
- Find out more on how to implement real mathematical optimization
- Run simulations
- compare results
Accounting
- Found a way to implement mathematical (with asumption)
- Ran some simulations