Learning transparent models from Data-driven Algorithms to Enhance Streaming Data Analysis

The aim of this project is to enable Bayesian filters to work in conjunction with the algorithms used to train neural networks, in both a supervised and unsupervised fashion to model dynamic and measurement models, thus allowing them the exploit prior knowledge of the system and analyse the behaviour of the system under these circumstances, and…