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 9 of 9 for “"Local Interpretable Model-Agnostic Explanations"”.
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ULIME: Uniformly weighted Local Interpretable Model-agnostic Explanations for Image Classifiers
… rapid development of complex machine learning models, there is uncertainty on how these models truly work. Their black-box nature restricts experts from evaluating models solely on standard numerical metrics, which may result in a model performing seemingly well on a dataset but for the wrong …
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Inductive logic programming with gradient descent for supervised binary classification
… interpretability has become a major concern for models making important decisions. In contrast to Local Interpretable Model-Agnostic Explanations (LIME), this thesis seeks to develop an interpretable model using logical rules, rather than explaining existing blackbox models. We extend recent …
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Multi-scale local explanation approach for image analysis using model-agnostic explainable artificial intelligence (XAI)
… for the broad adoption of deep learning based models such as Convolutional Neural Networks (CNN) is the lack of understanding of their decisions. Local Interpretable Model-agnostic Explanations (LIME) is an explanation method which produces a coarse heatmap as a visual explanation highlighting …
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A Multitask Deep Learning Framework for Clinical Decision-Making in Assisted Reproductive Technology
… pipeline evaluates classical statistical models, ensemble methods (XGBoost), and novel architectures, including TabPFN, an attention-based probabilistic model that achieved comparable performance to top-performing baselines. To enhance clinical trust, we apply SHapley Additive exPlanations …
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STUDYING PRODUCT REVIEWS USING SENTIMENT ANALYSIS BASED ON INTERPRETABLE MACHINE LEARNING
… (rule-based) and black-box opaque (BERT) models. We find that while the black-box model is more correlated with product ratings, there are interesting counterexamples where the sentiment analysis results by the glass-box model are better aligned with the rating. Next, we explore how well …
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The Role of Explainable Artificial Intelligence in Data Science [Il Ruolo dell'Intelligenza Artificiale Esplicabile nella Scienza dei Dati]
… automatico accelera la domanda parallela di modelli trasparenti e interpretabili. La tesi inizia con un'esplorazione approfondita dell'Intelligenza Artificiale Esplicabile (XAI), che include metodi specifici per modello e indipendenti dal modello. Questo comporta un'analisi dettagliata di …
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Causal and system-theoretic approaches to interpretable machine learning
… constraints. In such settings, machine learning models frequently fail to generalize and may even produce results that contradict well-established scientific principles. The lack of interpretability not only undermines trust but also hinders our ability to diagnose, debug, and improve these …
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Learning based algorithms for temperature control and fouling prediction in heat-exchangers
… temperature control and fouling resistance modeling and prediction. Designing robust and accurate temperature controllers for heat exchangers is very challenging primarily because of complexities associated with the synthesis of dynamics of industrial heat exchangers. It is practically …
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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