SMCPy

SMCPy is an open-source package for performing uncertainty quantification using a parallelized sequential Monte Carlo sampler.

SMCPy

I’ve been actively working with NASA Langley on developing improvements to their Sequential Monte Carlo sampler - specifically for finite element modeling applications. My contributions primarly focus on theoretical and development provements to the foward kernels of the SMC mutation step, implementing gradient-accelerated features suited for high-performance computing clusters, significantly improving computational efficiency.