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 8 of 8 for “"model confidence"”.
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Key challenges to model-based design : distinguishing model confidence from model validation
Model-based design is becoming more prevalent in industry due to increasing complexities in technology while schedules shorten and budgets tighten. Model-based design is a means to substantiate good design under these circumstances. Despite this, organizations often have a lack of confidence in the …
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Uncertainty and Generality of Transfer Learning Models in Predicting Signaling History
… often show extremely high or extremely low confidence, suggesting a need for methods to prevent overconfidence and better account for uncertainty. To generalize IRIS to broader cell-cell communication problems, we combined engineering and experimental approaches, integrating uncertainty …
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Towards a Reliable Deep Learning Framework for Prostate Cancer Diagnosis using Ultrasound
… patient outcomes. Developing deep learning (DL) models for PCa detection is hindered by noisy labels and cancer heterogeneity. The purpose of this work is to develop a clinically applicable framework for DL-based detection of PCa from ultrasound that is robust to noise and uncertainty inherent to …
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Similarity-Augmented Prediction Methods for Neural Machine Translation
Neural language models (LMs) are now the dominant approach to most tasks in natural language processing (NLP), including machine translation (MT). In spite of their success, studies have shown systematic problems in these models such as the high dispersal of probability mass across vastly many …
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Three Essays in Econometrics
… and specification testing for multivariate models, through the lens of model selection procedures in asset pricing. In the first chapter, I provide a model selection procedure for multivariate models, generalizing the model confidence set (MCS) procedure to systems of N>1 dependent …
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Automation of the γ-ray spectrometry setup of the Environmental Radioactive Laboratory at NRF-iThemba LABS
… responses, providing a solid foundation for model training and evaluation. Data preprocessing, feature handling, and visualization were carried out using Python and ROOT, ensuring consistency and reproducibility throughout the analysis pipeline. Two physics-inspired deep learning models, …
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New regolith mapping approaches for old Australian landscapes.
… and formulation of associated robust process models are in their infancy compared with geological and soil mapping, which have had a long history of development and refinement. Regolith mapping can be seen as a hybrid approach combining elements from the existing mapping disciplines of …