Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 94 for “"explainable AI"”.
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Towards Maintainable and Explainable AI Systems with Dataflow
… updating workflows, monitoring and operational maintenance of these systems. The experience of numerous practitioners shows that the translation of a well-performing machine learning model to a well-performing machine learning system is not easy. This thesis embarks on a quest to understand the …
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The Epistemology of Explainable AI: Historical and Conceptual Perspectives
L'abstract è presente nell'allegato / the abstract is in the attachment
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Explainable AI in Medical Imaging: An Interdisciplinary Translational Approach
… has grown increasingly challenging, making explainable AI (XAI) a crucial component of modern AI systems. The focus of this work is to integrate these new technologies alongside foundational methods of image processing to create tools that can be used by domain experts who are not …
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Explainable AI: A Unified Approach Based on Cooperative Game Theory
Explainable Artificial Intelligence (XAI) aims to enhance the interpretability of machine learning (ML) models, yet existing feature-based explanation methods remain fragmented across local and global approaches. This thesis presents a unified framework based on cooperative game theory to …
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Towards explainable AI: directed inference of linear temporal logic constraints
… These systems are subject to both logical constraints, which govern their safe operation and goals; and dynamical constraints, which describe their physical behavior. These time-dependent constraints can be described with linear temporal logic (LTL). In the case where the constraints are not …
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Explainable AI framework through Multi-Context Multi-Dimensional Graph Neural Network
… to surmount these obstacles. GNNs displayed a flair for harnessing the relational dynamics inherent in complex systems such as social media, focus groups, and literature explaining the symbiosis between sentiment, context, and digital community. These relationships were converted into dense …
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Advancing Pattern Detection, Theory Development and Decision Making with Explainable AI
The application of explainable artificial intelligence (XAI) methods in data-driven decision-making and computationally intensive theory development (CTD) is a subject of ongoing debate, particularly concerning how and whether these methods can be effectively employed, and how the reliability of …
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Explainable AI Methods For Enhancing AI-Based Network Intrusion Detection Systems
… developing advanced artificial intelligence (AI) techniques for intrusion detection systems (IDS). However, the reliance on AI for IDS presents challenges, including the performance variability of different AI models and the lack of explainability of their decisions, hindering the …
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Transparent Value Alignment: Foundations for Human-Centered Explainable AI in Alignment
… open challenge in artificial intelligence that aims to address this problem by enabling agents to infer human goals and values through interaction. Providing humans with direct and explicit feedback about this value learning process through approaches for explainable AI (XAI) can enable humans …
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C-XAI: Design Method for Explainable AI Interfaces to Enhance Trust Calibration.
Human-AI collaborative decision-making tools are on an accelerated rise in several critical application domains, such as healthcare and military sectors. It is often difficult for users of such systems to understand the AI reasoning and output, particularly when the underlying algorithm and logic …
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Prediction of Gravel Streambed Embeddedness Using Explainable AI and Machine Learning Techniques
… learning models using remotely sensed data and explainable artificial intelligence (XAI) to uncover important variables related to physical processes affecting embeddedness in Virginia (VA) and the United States (U.S.). The VA model used 1,125 embeddedness measurements from 906 sites provided by …
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IoT network Malicious Behaviour Profiling Based on Explainable AI Using LSTM and SHAP
… and identification profiling model using XAI. The proposed model introduces a novel feature selection techqnique with the XGBoost algorithm and a correlation-based feature selection technique to enhance efficiency. An optimized LSTM neural network enables accurate bot detection and …
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AI-based leakage prediction with uncertainty quantification and explainable AI for nuclear system
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01
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Why Are Some Watersheds More Sediment-Productive Than Others? An Explainable AI Approach
… watershed outlet per unit time, normalized by drainage area. Quantifying the spatial variability of both metrics is critical for sediment management and water quality protection, yet the drivers of SDR remain poorly constrained at continental scales. Here, we develop a data-driven framework to …
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Explainable AI for Social Good: Applications in Mental Health, Public Health Risk, and Environmental Traceability
The ubiquitous use of machine learning and AI technology in human-centered domains such as social networks, public health, sustainable trade, and environmental forensics indicates a significant need for an adaptive, interpretable, and generalizable approach in predictive modeling. With the …
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