Neue Zürcher Zeitung | A data lake, not a data swamp [In German]

The lack of transparency of black-box models is a fundamental problem in modern Artificial Intelligence and Machine Learning. This work focuses on how to unbox deep learning models for image classification problems.

LeafSim is an example-based explainable AI (XAI) technique for decision tree-based ensemble methods, explaining model predictions by identifying training data points that most influence a given prediction.

The WSL and the SDSC are actively working towards the development and the study of the benefits of machine learning approaches for facilitating biodiversity assessments.

We need complex models that accurately represent the feedbacks between different processes and compartments to inform us how a perturbation in one component may affect other components of the coupled climate-earth surface system that are relevant to us.

The lack of transparency of black-box models is a fundamental problem in modern Artificial Intelligence and Machine Learning. This work focuses on how to unbox deep learning models for image classification problems.