Comments (3)
You can try setting max_num_improvement_loops=0 to prevent too much refinement.
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Maybe first analytically calculate the number of posterior modes for the 5D problem to appreciate the difficulty of this problem. Other samplers giving answers quickly does not mean their answers are reliable, which is something you may care about.
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It may be 486 modes in 5 dimensions.
Since it is a product over the parameters, and each axis has a cos(x/2) function which has three +1 peaks,
I get 3^d positive interferences and then as many for negative interferences (-1 * -1 is also a peak).
This can be solved by convergence assuming the modes are similar, but if you set cluster_num_live_points (default 40), then it will want to add more live points for each newly found cluster.
Closing this for now, please reopen if there is something more to discuss / resolve.
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Related Issues (20)
- store dimensionality in points file HOT 1
- refine slow warning
- Ultranest 3.6.1 does not install in new .venv environment HOT 14
- Difficulty installing Ultranest versions prior to 3.6.2 HOT 4
- Feature request/bug: returning float32 from log-likelihood fn with PopulationSliceSampler HOT 7
- MPI fails with likelihoods that have plateaus HOT 4
- Access chains / intermediary results for run in progess? HOT 1
- `saved_logwt_bs` error after completion HOT 1
- How to Resume Execution with Only the results/points.hdf5 File? HOT 1
- Vectorised sampling and memory consumption HOT 4
- [Question] Constant efficiency mode HOT 2
- tregion argument is not supported by dychmc dychmc __next__ function HOT 5
- Reproducibility of UltraNest fits HOT 2
- Missing documentation for results dictionary HOT 4
- Conda installer does not work for Apple OSX-arm64
- Ultranest version 4 HOT 4
- Add ESS calculation to static version results HOT 2
- ARM bug: overflow from excessive live points HOT 8
- 4.1.6 performs worse HOT 18
- num_live_points_missing error when running ultranest in parallel via mpiexec HOT 8
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