Comments (2)
Also, I should consider this: MCMC can also track blobs, the 2nd returned parameter(s) in emcee's LnLike functions. approxposterior should include the functionality to handle them, either by saving them or ignoring them, depending on the user's needs.
from approxposterior.
I think the answer to this question is no, but I did add the functionality handle blobs on the dev branch.
from approxposterior.
Related Issues (20)
- Optimize the GP less HOT 1
- conda installation is broke HOT 2
- Multiprocessing is slow: too much overhead spinning up new processes HOT 2
- Let users set the name of the output files HOT 1
- Scaling parameter values to improve GP hyperparameter optimization HOT 1
- Use other regression algorithms besides the GP for logprobability predictions HOT 1
- Implement Bayesian Optimization HOT 2
- Cross-Validation to select GP hyperparameters HOT 1
- Explore approxposterior parallelization paradigm HOT 1
- Utility functions for training set initialization HOT 1
- Add bounds, scale to ApproxPosterior object? HOT 1
- Can't clone from [email protected]:dflemin3 HOT 1
- Use latin hypercube sampler to initialize GP optimizations HOT 1
- Add MultiNest for posterior retreival HOT 1
- Parallel approxposterior using python 3.8+ multiprocessing
- Add a warning for when the GP optimization optGPEveryN > m HOT 1
- Standardize code formatting
- Don't use nbsphinx_prompt_width to hide prompts HOT 1
- Single parameter inference causes ValueError
- Unnecessary creation of a new GP object in `findNextPoint`
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from approxposterior.