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.
Results
Showing 1 to 9 of 9 for “"generative deep learning"”.
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Generative deep learning: Towards better visual representations and multimodal
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms
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Designing Novel DNA-Binding Proteins with Generative Deep Learning
Protein-DNA interactions play a critical role in various biological processes, such as gene regulation and genome maintenance. Designing protein backbones specifically tailored for DNA binding remains a challenging task, requiring the exploration of novel computational approaches. This thesis …
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Improved hyperspectral classification of vegetation through generative deep learning models.
… the intra/inter-class relationship with deep generative sample transformation. For objective one the last two decades of hyperspectral vegetation classification literature was systematically reviewed, specifically focusing on waveband/feature selection. Additionally, waveband selection …
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Information and generative deep learning with applications to medical time-series
… There are wide- ranging complexities involved in learning such insights from longitudinal data, including a lack of a universal accepted framework for understanding causal influence in time-series, issues with poor quality data segments that bias downstream tasks, and important privacy concerns …
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Magnetic and Superconducting Materials Discovery: Employing Data Science, Natural Language Processing and Machine Learning
… scientific literature. Application of machine learning to these data enables exploration of structure-property trends and thereby enriches the materials discovery process. Chapter 1 reviews the current literature on materials informatics and materials discovery. This includes the introductory …
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Decentralized AI for Methylation Data with Applications to Precision Health
… and the development of robust machine learning models. This thesis proposes a decentralized artificial intelligence framework for analyzing DNA methylation data, enabling institutions to collaboratively train models without exchanging sensitive information. By taking advantage of …
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Three-dimensional wildland fuel mapping with remote sensing and machine learning
… LiDAR (ALS, TLS; respectively) and machine learning to make fine scaled predictions of fuels beneath the canopy. In my first chapter I use a gradient boosting regressor to boost the signal of ALS at the surface floor by using the ALS signal itself as features. I demonstrate that this method …
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Perturbation Modeling for Molecular Design of Protein Tyrosine Kinase Inhibitors using Unsupervised Machine Learning
… tools for novel molecule discovery. In specific, generative deep learning models have excelled as tools to aid in navigating the large space of known molecules and in the creation of new molecules. These models are fed various representations of molecules as inputs and learn to perform a variety …
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Advances in statistical post-processing of weather forecasts, probabilistic forecasting, and modelling of extreme events
… suited to extremes. Thus, I propose a number of generative deep learning approaches for the modelling of the dependence structure of multivariate extremes. I showcase on simulated and real data the effectiveness of these methods and contrast them with a classical parametric approach. Whilst this …