gaussian-mixture-models

Flash-GMM introduces a fused Triton kernel for Gaussian Mixture Models that achieves 20x speedup and enables training on datasets 100x larger on a single GPU, making soft clustering a viable drop-in replacement for k-means in approximate nearest neighbor search.

This paper introduces a probabilistic polygonal representation for plane curves using Gaussian Mixture Models, preserving local tangent, normal, and arc length while encoding uncertainty in the normal direction. The framework applies to various plane curves and supports uncertainty-aware geometric modeling for CAD, robotics, and trajectory planning.