Current convolutional networks work with inefficient pixel-wise image representation, which does not provide almost any invariance. This leads to using very large training sets and massive augmentation.

The project will develop a new family of models for identification of tail risks in financial markets from possibly large datasets using deep learning algorithms. Our newly developed methods will allow us to revisit several classical problems in empirical asset pricing. We believe that the results will be of fundamental character and will open number of questions.

The main aim of the EECONE project is to reduce e-waste on a European scale. The environmental impact arising from e-waste can thus be reduced by working in three principal areas: 1) Increase service lifetime of electronic products by application of ecodesign guidelines for increasing their reliability and their repair rate, thereby reducing the volume of e-waste.

The project focuses on the protection of video and image content and looks at ways to prevent illegal sharing. It will explore how artificial intelligence methods can circumvent these protections and the challenges of applying protection to large volumes of data.

Decentralized finance has been often synonymized with cryptocurrencies, cryptoassets, or even simply with Bitcoin not only in the public perception but to a high degree also in financial research. This project aims to dive deeper into decentralized finance and in a comprehensive manner explore and describe its structural aspects.

Project HiPE brings together 13 participants covering the whole value chain, to develop a new highly energy-efficient, cost-effective, modular, compact and integrated wide bandgap (WBG) power electronics solutions for the next generation of battery electric vehicles (BEV), and to facilitate a significant market penetration of WBG in the automotive sector.

The aim of the project is to promote understanding of complex interactions and the dynamics of decision making (DM) under complexity and uncertainty. The theory under consideration should be applicable to dynamic DM and interaction within a flat structure without any coordination. It will support modelling a living agent acting within a complex network of interacting heterogeneous agents.