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They only return zero for all inputs.
```python
import sys
sys.path.append("..")
from sklearn.datasets import *
data = load_iris()
X = data.data
y = data.target
X_train, X_valid, y_tra…
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It would be nice to use something like: use Monte Carlo and immediately receive a formula for that.
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## Summary
Monte Carlo simulation is widely used in financial risk management to forecast potential losses or gains. This statistical method models the uncertainties in financial markets by simulatin…
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Below I am tracking a PR that **we merged in an incomplete state**. Because the cleaning process drops all PRs we decided to merge this PR anyways while keeping track of the necessary tasks/possible i…
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Is there any example of any monte carlo simulation using the sky130A ngspice libs? The only example of monte carlo simulation I've seen for sky130A was the one which comes with the xschem examples. I'…
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@davidthomas5412 Let's start with the simplest possible inference: simple Monte Carlo. We'll need the ForegroundCatalog to be able to `set_prior` and then `draw_halo_masses`, and then we'll need to `c…
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It would be nice to make the monte carlo tests happen with multiprocess to speed up computation time. This is something I will start working on.
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Monte Carlo crashes FFM when certain inputs are used. The two input files are identical except for a very slight difference in air temperature and surface dead fuel moisture content, but Faulty.txt wi…
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Hamiltonian Monte Carlo (HMC) is a widely used, gradient based, MCMC algorithm, that is the backbone of Stan's inference. I plan to implement it for monad-bayes. Todos (checkboxes indicate things done…