Remaining Useful Life (RUL) estimation is directly related with the application of predictive maintenance. When RUL estimation is performed via data-driven methods and Artificial Intelligence algorithms, explainability and interpretability of the model are necessary for trusted predictions. This is especially …

Explainable artificial intelligence (xAI) is seen as a solution to making AI systems less of a “black box”. It is essential to ensure transparency, fairness, and accountability – which are especially paramount in the financial sector. The aim of this study was a preliminary investigation of the perspectives …

B4B is a multi-year, multi-stakeholder project focused on developing methods to harness big data from smart meters, building management systems and the Internet of Things devices, to reduce energy consumption, increase comfort, respond flexibly to user behaviour and local energy supply and demand, and …

Powerpresentatie tijdens CORAL symposium.

Multilevel models (MLMs) are increasingly deployed in industry across different functions. Applications usually result in binary classification within groups or hierarchies based on a set of input features. For transparent and ethical applications of such models, sound audit frameworks need to be developed. …

Toelichting op het rapport Opgave AI van de Wetenschappelijke Raad voor het Regeringsbeleid (WRR).

Founded in 2014, Dashmote was a rapidly growing and globally operating Software as a Service (SaaS) company based on its Artificial Intelligence (AI), natural language processing and visual recognition technologies. The founders aimed to guide people toward success in an AI and data-driven world by improving …

Key to reinforcement learning in multi-agent systems is the ability to exploit the fact that agents only directly influence only a small subset of the other agents. Such loose couplings are often modelled using a graphical model: a coordination graph. Finding an (approximately) optimal joint action for …

We present a novel architecture for an AI system that allows a priori knowledge to combine with deep learning. In traditional neural networks, all available data is pooled at the input layer. Our alternative neural network is constructed so that partial representations (invariants) are learned in the …

Beschouwing van mogelijkheden en onmogelijkheden bij de inzet van simulaties om AI-modellen te trainen.