5 papers
Uncertainty-Guided Expert-AI Collaboration for Efficient Soil Horizon Annotation
Teodor Chiaburu, Vipin Singh, Frank Haußer +1
Uncertainty quantification is essential in human-machine collaboration, as human agents tend to adjust their decisions based on the confidence of the machine counterpart. Reliably…
SoilNet: A Multimodal Multitask Model for Hierarchical Classification of Soil Horizons
Vipin Singh, Teodor Chiaburu, Einar Eberhardt +4
Recent advances in artificial intelligence (AI), in particular foundation models, have improved the state of the art in many application domains including geosciences. Some specifi…
Evaluating Time Series Models for Urban Wastewater Management: Predictive Performance, Model Complexity and Resilience
Vipin Singh, Tianheng Ling, Teodor Chiaburu +1
Climate change increases the frequency of extreme rainfall, placing a significant strain on urban infrastructures, especially Combined Sewer Systems (CSS). Overflows from overburde…
Uncertainty Propagation in XAI: A Comparison of Analytical and Empirical Estimators
Teodor Chiaburu, Felix Bießmann, Frank Haußer
Understanding uncertainty in Explainable AI (XAI) is crucial for building trust and ensuring reliable decision-making in Machine Learning models. This paper introduces a unified fr…
Confident Teacher, Confident Student? A Novel User Study Design for Investigating the Didactic Potential of Explanations and their Impact on Uncertainty
Teodor Chiaburu, Frank Haußer, Felix Bießmann
Evaluating the quality of explanations in Explainable Artificial Intelligence (XAI) is to this day a challenging problem, with ongoing debate in the research community. While some…