aschampion / aschampion/diluvian
Optional noise/dropout in mask input channel for robustness training
Open
enhancement
- Dominant language
- Python
- Stars
- 26
- Forks
- 13
- PR merge metrics
- No merged PRs in 30d
Description
This issue has no description.
Contributor guide
Research direction
The issue body names no files, tests, or entry points. Start by locating the mask input channel and the training path in the Python code, then determine how an optional noise or dropout setting should be exposed and verified. Done means robustness training can apply the requested optional perturbation without changing the default behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100