Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …

The role of data in building AI systems has recently been significantly magnified by the
emerging concept of data-centric AI (DCAI), which advocates a fundamental shift from model …

Chloride corrosion is a key factor affecting the life of marine concrete, and surface chloride
concentration is the main parameter for analyzing its durability. In this paper, we first …

Modern deep learning methods have long been considered black boxes due to the lack of
insights into their decision-making process. However, recent advances in explainable …

Even though Shapley value provides an effective explanation for a DNN model prediction,
the computation relies on the enumeration of all possible input feature coalitions, which …

Given the complexity and lack of transparency in deep neural networks (DNNs), extensive
efforts have been made to make these systems more interpretable or explain their behaviors …

Recent advancements in explainable machine learning provide effective and faithful
solutions for interpreting model behaviors. However, many explanation methods encounter …

Explainable artificial intelligence (XAI) techniques are used to understand the rationale
behind the decision-making of machine learning models. In addition to the need for model …

In the evolving landscape of interpretable machine learning (ML) and explainable artificial
intelligence, transparent and comprehensible ML models are crucial for data-driven decision …

Currently, reinforcement learning, the interpretability of the algorithm is a challenge. The lack
of interpretability limits the use of reinforcement learning limited when facing agents in the …