A Jax-based differentiable Monte Carlo estimator with applications to differentiable simulation, computational geometry, and topology optimization.
Project description
Fiber Monte Carlo
Fiber Monte Carlo (FMC) is a differentiable variant of the simple Monte Carlo estimator designed with low-dimensional geometric-oriented applications in mind. The methodological and theoretical aspects of FMC are outlined in the accompanying paper, 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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