The use of algorithmic tools by journalists for information-gathering has received particular attention in recent years. While it might facilitate the research process, there are also concerns about their impact on journalism. Based on reconstruction interviews with 27 journalists, we first answer the …

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. …

The goal of this study was to develop an automated monitoring system for the detection of pigs’ bodies, heads and tails. The aim in the first part of the study was to recognize individual pigs (in lying and standing positions) in groups and their body parts (head/ears, and tail) by using machine learning …

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.