Browsing Department of Computational and Data Sciences (CDS) by thesis submitted date"2025"
Now showing items 1-3 of 3
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Algorithmic Approaches to Pangenome Graph Problems
The human reference genome serves as a foundational baseline for comparing newly sequenced human genomes. With the growing availability of high-quality human genome assemblies, there is now an opportunity to modernize the ... -
Improving hp-Variational Physics-Informed Neural Networks: A Tensor-driven Framework for Complex Geometries, and Singularly Perturbed and Fluid Flow Problems
Scientific machine learning (SciML) combines traditional computational science and physical modeling with data-driven deep learning techniques to solve complex problems. It generally involves incorporating physical ... -
Unsupervised Test-time Adaptation for Patient-Specific Deep Learning Models in Medical Imaging
Deep learning (DL) models have achieved state-of-the-art results in multiple medical imaging applications, resulting in the widespread adoption of artificial intelligence (AI) models for radiological workflows. Despite ...