Teleparallel gravity (TG) has significantly increased in popularity in recent decades, bringing
attention to Einstein's other theory of gravity. In this Review, we give a comprehensive …

Abstract Explainable Artificial Intelligence (XAI) is an emerging research field bringing
transparency to highly complex and opaque machine learning (ML) models. Despite the …

Recent large language models (LLMs), such as ChatGPT, have demonstrated remarkable
prediction performance for a growing array of tasks. However, their proliferation into high …

Recent deep-learning models have achieved impressive prediction performance, but often
sacrifice interpretability and computational efficiency. Interpretability is crucial in many …

Methods based on machine learning have recently made substantial inroads in many
corners of cosmology. Through this process, new computational tools, new perspectives on …

Deep Learning has already been successfully applied to analyze industrial sensor data in a
variety of relevant use cases. However, the opaque nature of many well-performing methods …

Subgroup discovery is a descriptive and exploratory data mining technique to identify
subgroups in a population that exhibit interesting behavior with respect to a variable of …

Measuring biases of vision systems with respect to protected attributes like gender and age
is critical as these systems gain widespread use in society. However, significant correlations …

The recent surge in highly successful, but opaque, machine-learning models has given rise
to a dire need for interpretability. This work addresses the problem of interpretability with …

Recent deep-learning models have achieved impressive predictive performance by learning
complex functions of many variables, often at the cost of interpretability. This chapter covers …