semvec/pypi-packages huggingface dataset:
fibermc 0.0.4
A Jax-based differentiable Monte Carlo estimator with applications to differentiable simulation, computational geometry, and topology optimization.
License: MIT
Requires Python: >=3.8
Keywords: computational geometry, implicit differentiation, jax, optimization, topology optimization

# Fiber Monte Carlo 

Fiber Monte Carlo (FMC) is a differentiable variant of the [simple Monte Carlo](https://en.wikipedia.org/wiki/Monte_Carlo_method) estimator designed with 
low-dimensional geometric-oriented applications in mind. The methodological and theoretical aspects of FMC are outlined in the accompanying [paper](https://openreview.net/pdf?id=sP1tCl2QBk), but this Python package contains implementations of a variety of general-purpose estimators with FMC as the underlying method, as well as utilities specific applications like computational geometry, differentiable rendering and topology optimization.