fibermc

Name	fibermc JSON
Version	0.0.4 JSON
	download
home_page	None
Summary	A Jax-based differentiable Monte Carlo estimator with applications to differentiable simulation, computational geometry, and topology optimization.
upload_time	2024-12-10 19:42:08
maintainer	None
docs_url	None
author	None
requires_python	>=3.8
license	MIT
keywords	computational geometry implicit differentiation jax optimization topology optimization
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bugtrack_url
requirements	No requirements were recorded.
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            # 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. 

            

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