Distribution-free uncertainty quantification for kernel methods by gradient perturbations

Machine Learning - We propose a data-driven approach to quantify the uncertainty of models constructed by kernel methods. Our approach minimizes the needed distributional assumptions, hence,...     

An effectiveness analysis of altmetrics indices for different levels of artificial intelligence publications

Scientometrics - Altmetrics indices are increasingly applied to measure scholarly influence in recent years because they can reflect the influence of research outputs more timely comparing with...     

Context-Based Path Prediction for Targets with Switching Dynamics

International Journal of Computer Vision - Anticipating future situations from streaming sensor data is a key perception challenge for mobile robotics and automated vehicles. We address the problem...     

Tuning the Operating Band of an Artificial Magnetic Conductor

Journal of Communications Technology and Electronics - Approximate formulas for calculating the coefficient of reflection from an artificial magnetic conductor (AMC) based on a capacitive lattice...