Matthias J. Ehrhardt
Combining theory, modelling, data, and computation to unlock the next generation of deep learning
Machine learning, in particular Deep Learning (DL) based on ‘neural networks’, is one of the fastest growing areas of modern science and technology, which has potentially an enormous and transformative impact on all areas of our lives. The applications of DL embrace many disciplines such as biomedical sciences, computer vision, the physical sciences, the social sciences, speech recognition, gaming, music and finance.
However, alongside this explosive growth has been a concern about the lack of understanding behind DL and the way that DL based algorithms make their decisions. This leads to a lack of trustworthiness in the use of some of these algorithms. A reason for this is that the huge successes of Deep Learning are not all well understood, the results are sometimes mysterious, and there is often a lack of a clear link between the data training DL algorithms, and the decisions made by those algorithms. Maths4DL aims t
Matthias J. Ehrhardt