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https://ubc-vision.github.io/3dgs-mcmc/
This paper introduced a new conceptual model for how to view the process of gaussian splat optimization and then used that to guide several improvements to t…
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https://ubc-vision.github.io/3dgs-mcmc/
This paper introduced a new conceptual model for how to view the process of gaussian splat optimization and then used that to guide several changes to the or…
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**_Comments by @longye-tian:_**
## Code
- [x] Change global variables to `default_param` (i.e. `default_μ`).
- [x] Distinguish the function name in the exercise solution and the one in the mai…
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**Describe the feature you'd like**
A new simulator which implements Monte Carlo sampling to perform trajectory-based noise simulation. This would be `shots>0` *only* but would allow qubit counts up …
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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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In this use case, we ought to develop ChatRnD teams of AI-Agents capable of developing and presenting novel use case of Monte Carlo Algorithm.
As part of this use case the ChatRnD AI-Agents should c…
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Everyone loves the fact that RocketPy can be quite easily wrapped to run Monte Carlo simulations to carry on dispersion analysis.
However, this experience quickly becomes hard as the analysis compl…
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A question that occasionally comes up is how to implement Monte Carlo simulations. That's a broad category that can mean a lot of different things. It's worth considering whether we can add features…
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Hey
**Background**
I am looking at scenarios where the cosmic rays propagate close to the source in environments where advective transport dominates over diffusion for $E\lesssim1~\mathrm{EeV}$. As …