Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Tasks for first working prototype #1

Open
18 of 22 tasks
fritzo opened this issue Sep 29, 2021 · 0 comments
Open
18 of 22 tasks

Tasks for first working prototype #1

fritzo opened this issue Sep 29, 2021 · 0 comments
Labels
enhancement New feature or request

Comments

@fritzo
Copy link
Member

fritzo commented Sep 29, 2021

  • parametrize coefficients
  • handle constraints
  • make github repo
  • add syntactic sugar for constraints
  • implement block gibbs
  • pairwise / quadratic / cross terms
  • ingest tsv file in example.py (fritz)
  • move to HMC (fritz)
  • port notebook pipeline to scripts
  • add helpers to specify and validate initial data
    • {"sequences": _, "batch_id": _, "response": _}
  • add some unit tests (fritz)
  • wrap things up in higher-level components with validation logic (fritz)
    • e.g. wrap thompson_sample() in get_next_batch()
  • improve README.md (fritz)
  • improve docstrings (fritz)
  • add tf8 plots to README (martin)
  • make tf8 example reproducible, add plots (martin)
  • make observation model configurable
    • currently a quantized response model
    • maybe add a couple options specified by string?
  • extend model language to include user-provided features
    • rename FEATURES to GROUPS or FEATURE_BLOCKS?
    • continuous-valued embeddings
    • cluster ids
  • model criticism (martin)
    • assess model fit, heldout error, find outliers
    • explore which features are active (rank or visualize?)
  • warnings and errors
    • warn if GIBBS_BLOCKS or FEATURE_BLOCKS are too large
    • print number of parameters and the user-facing code that led to the most parameters
  • choose better hyperparameter priors
  • support coefficient sparsity (fritz)
    • allow Laplace priors for coefficients (probably default to this)
    • use different scale parameters for single vs pairwise coefficients
@fritzo fritzo added the enhancement New feature or request label Sep 29, 2021
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

1 participant