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At the moment this can be hacked by doing `MeasureFock` and converting any nonzero results to a value of 1. However, there is likely a simpler way to implement these things by leveraging sampling algo…
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Currently, the Default Sampling worker operates in the following steps every time `obtain_samples` is called:
```
1) reset environment
2) step environment and collect samples `n` times
3) post p…
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### Subject of the issue
We have some explicit gradient functions for gaussian distribution https://github.com/pgmpy/pgmpy/blob/dev/pgmpy/sampling/base.py#L97. If we replace this with one of the auto…
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We might want to add a comparison oriented tutorial for various sampling algorithms at some point. Two previous tutorials that I find relevant are
- https://github.com/mlss-2019/tutorials/blob/mas…
yebai updated
4 years ago
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### Feature request
The generate function is decorated with @torch.no_grad() and thus can't be used for model training. It would be better to make calculating gradients optional, rather than imposs…
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```random_shuffle``` was removed in c++17 and you use c++17.
```
/usr/bin/c++ -DCGAL_USE_GMPXX=1 -D_LIB -D_USE_BOOST -D_USE_EIGEN -D_USE_FAST_CBRT -D_USE_FAST_FLOAT2INT -D_USE_NONFREE -D_USE_OPENG…
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Add tests for generating a large number of samples and check if the probability distribution is approximately same as expected.
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### What is the problem you're trying to solve
I'm very interested in finding the right balance of compression between zstd, gzip, and different levels of compression to reduce the startup time of …
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I usually start scripting my analyses with other algorithms, such as meanfield, make sure the script is running smoothly and without errors, and only then replace meanfield with "sampling" and run the…
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@eb8680 had an implementation for single site Metropolis Hastings in #61. Let us resolve the issues raised in the PR, and reinstate the algorithm. This is also needed to build other algorithms like An…