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Improving sampling techniques #84

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NicoRenaud opened this issue Mar 9, 2021 · 0 comments

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NicoRenaud commented Mar 9, 2021 •

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We could go beyond Metropolis Hasting to do the sampling. A few candidates are :

Hamiltonian Monte Carlo (already sort of implemented sampler/hamiltonian.py)
An efficient QMC specific sampling https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.71.408 Would be great to implement this one !
Using PyMC3 https://docs.pymc.io/ A lot is implemented here but I don't know if we can use it here as our objective function is a pytorch object. It would be great to look into it as it would bring a lot of different methods !

For each method it would be great to have a small benchmark of their perf and when possible some having them as efficient as possible

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