Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
— We present a comparative study of two spatially resolved macroscopic models of an autonomous robotic swarm. In previous experiments, the collective behavior of 15 autonomous sw...
Gene regulatory network model is the most widely used mechanism to model and predict the behavior of living organisms. Network Component Analysis (NCA) as an emerging issue for unc...
Accurate modeling of communication is a necessary part of system level design for real-time safety-critical applications. For efficient prediction of a system’s performance, Tra...