IEEE

Learning-Based Model Predictive Control With High-Probability Safety Using Gaussian Mixture Models

Abstract: This article introduces a learning-based model predictive control (MPC) framework that leverages Gaussian mixture models (GMMs) to address dynamic system uncertainties effectively. To ...
IEEE

Enhancing Gaussian Mixture Model Efficiency Through Covariance Matrix Optimization, Singular Value Decomposition, and Block Toeplitz Matrices

Abstract: Gaussian Mixture Models (GMMs) are widely used for clustering, density estimation, and pattern recognition. Despite their versatility, GMMs often face computational challenges, particularly ...
GitHub

[CVPR 2025] UniPre3D: Unified Pre-training of 3D Point Cloud Models with Cross-Modal Gaussian Splatting

UniPre3D is the first unified pre-training method for 3D point clouds that effectively handles both object- and scene-level data through cross-modal Gaussian splatting. Our proposed pre-training task ...