Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …

Material intensity coefficient (MIC) is vital for material stock accounting in the field of
industrial ecology. However, the categorization of MIC varies across regions especially for …

We use recent explainable artificial intelligence (XAI) based on SHapley Additive
exPlanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), and Light …

Since recommender systems play an important role in our online experience today and are
involved in a wide range of decisions, multiple stakeholders are requesting explanations for …

Hydrological models are valuable tools for developing streamflow predictions in
unmonitored catchments to increase our understanding of hydrological processes. A recent …

Although modern machine learning and deep learning methods allow for complex and in-
depth data analytics, the predictive models generated by these methods are often highly …

The prediction of hydrologic conditions in watersheds has manifold applications, ranging
from flood disaster preparedness to water supply and environmental flow management. In …

Cancer immune evasion contributes to checkpoint immunotherapy failure in many patients
with metastatic cancers. The embryonic transcription factor DUX4 was recently characterized …

In The hitchhiker's guide to responsible machine learning, Biecek, Kozak, and Zawada (here
BKZ) provide an illustrated and engaging step-by-step guide on how to perform a machine …

In recent years, a new discipline known as Explainable Artificial Intelligence (XAI) has
emerged, which has followed the growing trend experienced by Artificial Intelligence over …