Comments (4)
rlouf
commented on May 30, 2024
Note: this PR in PyMC3 improves the warmup by waiting for the chain to be in the typical set before adapting the mass matrix.
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rlouf
commented on May 30, 2024
Note: simplify the implementation of the dual averaging algorithm as I did in aehmc.
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rlouf
commented on May 30, 2024
Looks like the acceptance probability currently returned is not the expected value, which may explain the problem with the warmup.
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rlouf
commented on May 30, 2024
The Introduction.ipynb notebook was the last place where there was an issue with adaptation (to my knowledge). I updated the notebook in a29272d and found that the resulting kernel samples correctly 👍
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Related Issues (20)
- 👋 Blackjax Meeting -
- 👋 Blackjax Meeting -
- BlackJAX Paper HOT 3
- CHMC from A Family of MCMC Methods on Implicitly Defined Manifolds
- 👋 Blackjax Meeting -
- Removing high-level API classes HOT 4
- 👋 Blackjax Meeting -
- test_chees_adaptation fail with jax 0.4.26 HOT 2
- DeprecationWarning from jax 0.4.27 HOT 2
- Blackjax has an implicit dependence on "jax>=0.4.25" and "jaxlib>=0.4.25" HOT 2
- window_adaptation excessive memory usage HOT 2
- Numerical test `test_chees_adaptation` fails on `aarch64-linux` HOT 4
- Improvements to `run_inference_algorithm`
- Adjusted MCLMC
- Generalize tuning algorithm for adjusted MCLMC to other samplers
- Add Omelyan integrator
- Add some metadata to integrators and export coefficients HOT 3
- Nightly build is failing
- 👋 Blackjax Meeting -
- Ability to pass low-rank mass matrices HOT 1
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