This section contains code implementations for various academic papers. Each project is designed to offer a practical perspective on the theoretical contributions of the respective papers, focusing on core methods and innovative techniques.
Implementation of spherical structured features for Gaussian Processes to improve spatial data modeling.
Random Features Kernel method for scalable kernel approximations in machine learning.
Experiments exploring guided dropout techniques to improve neural network generalization.