consistent treatment of `dt` parameter
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 124
- Forks
- 24
- Avg merge
- 19h 32m
- Merged PRs (30d)
- 60
Description
Two aspects to this:
1. We need to allow explicitly choosing the `dt` parameter for forward simulation, which goes into construction of random variables.
2. The `dt` which underlies the simulations for trained networks, specifically the ones we make available through Huggingface, has to be respected in the construction of our models.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files or tests are named. Start by locating forward-simulation random-variable construction and the model-building path for trained networks exposed through Hugging Face, then trace how each currently determines dt. Done means an explicitly selected forward-simulation dt is honored and the trained models consistently use the dt underlying their simulations.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- huggingface, python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100