7 citations · 7 across the 1 of their papers we have counts for
4 papers
Large Language Models for Automated Cross-Domain Machine Learning Task Type Identification: A Benchmark Dataset and Evaluation
Petros Tsialis, Steffen Limmer, Tobias Rodemann +1
Machine learning task type identification is essential for constructing valid ML pipelines, yet in practice it is typically specified manually. We investigate whether large languag…
A Comprehensive Perspective on Explainable AI across the Machine Learning Workflow
George Paterakis, Andrea Castellani, George Papoutsoglou +2
Artificial intelligence is reshaping science and industry, yet many users still regard its models as opaque "black boxes". Conventional explainable artificial-intelligence methods…
Predicting and Explaining Traffic Crash Severity Through Crash Feature Selection
Andrea Castellani, Zacharias Papadovasilakis, Giorgos Papoutsoglou +5
Motor vehicle crashes remain a leading cause of injury and death worldwide, necessitating data-driven approaches to understand and mitigate crash severity. This study introduces a…
A Real-World Energy Management Dataset from a Smart Company Building for Optimization and Machine Learning
Jens Engel, Andrea Castellani, Patricia Wollstadt +9
We present a large real-world dataset obtained from monitoring a smart company facility over the course of six years, from 2018 to 2023. The dataset includes energy consumption dat…