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Implement a Low-Discrepancy Sequence Generator
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### What happened?
Here are the first 4 points of the Faure sequence in the current's master:
| | y0 | y1 |
|---|---|---|
|0 | 0.5 | 0.5|
|1 | 0.25 | 0.75|
|2 | 0.75 | 0.25|
|3 | 0.125 | 0.…
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# Cube/cylinder/ball mappings
show some maps and plots of volume distortion
[http://marc-b-reynolds.github.io/math/2017/01/27/CubeBall.html](http://marc-b-reynolds.github.io/math/2017/01/27/CubeBall…
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How hard would it be to implement a library to generate pseudorandom numbers or values from a low-discrepancy sequence on the device? Ideally you'd have have each `Exp` getting its own values in paral…
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I'd like to use GoldenSequences.jl for quasi-random (low-discrepancy) sequences, but need it to work with AbstractRNG methods such as `rand`; is there a way to do this?
ghost updated
3 years ago
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I was surfing Wikipedia one night when I came across the page on [low-discrepancy sequences](https://en.wikipedia.org/wiki/Low-discrepancy_sequence), or subrandom numbers. These are sequences designed…
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# Square/Disc mappings
a visualization of area/shape distortions and point distributions
[http://marc-b-reynolds.github.io/math/2017/01/08/SquareDisc.html](http://marc-b-reynolds.github.io/math/2017…
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It looks like currently only RNG -based sampling is supported. As discussed in https://github.com/SciML/Integrals.jl/issues/11 Cuba supports using QMC. It is also supported in https://github.com/ranja…
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GMM introduces bias to the sampler. Two ways to remedy this.
1. slice sampling
- train gmm
- define the lowest score from the trained gmm on expanded samples as the threshold
- generate samples from …
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It would be nice to support parallelization, simply by exposing the `skip` feature of generators like Sobol.jl. That is, if you want to evaluate on 1000 processors with 2^15 points each, you could p…