Bayesian networks are widely valued in artificial intelligence for their capacity to provide interpretable, probabilistic models of complex systems, particularly in settings marked by uncertainty. Robustness and explainability ...

Predictive policing is known to carry the risk of feedback loops that can amplify existing biases. While these loops have received considerable attention in academic research, they remain under-explored in other policing ...

Spin qubits have attracted significant attention in quantum computing due to their long coherence times and compatibility with semiconductor fabrication processes. However, quantum non-demolition (QND) readout of spin ...

Large Language Models (LLMs) show promise for generating programming hints, but current systems largely ignore behavioral data from student programming sessions. This thesis investigates whether integrating contextual ...

This thesis investigates whether multitask learning can improve factual grounding in automated radiology report generation using Large Vision-Language Models. We adapt LLaVA-OneVision-7B with QLoRA for chest X-ray report ...

We investigate the possibility of formalizing the proof of the conservativity of TB in Halbach [1, p. 55f], in the interactive theorem prover Lean. Lean is based on dependent type theory, which has a natural connection to ...

Facial action unit (AU) detection struggles with the lack of 3D information from the common way of detection, using 2D images. This paper leverages 3D face reconstruction models, parametric facial data, and other multi-view ...

Due to the ongoing labour shortage, it is increasingly important for organizations to retain and nurture employees. As rewards are directly linked to work motivation, understanding how employees evaluate job-related rewards ...

Despite growing efforts to tackle gender inequality, discrepancies between men and women remain commonplace in the workplace. This experimental study examined how executives’ behaviour (status quo legitimising vs. status ...