Rasmus Kleist Hørlyck Sørensen
Scalable Algorithms for Constrained Gaussian Process Regression
Abstract: Gaussian process regression is a widely used Bayesian framework...
Johanne Badsberg Overgaard
Paying Attention to the Attention: Universal Annotation of Biological Sequences using Large Language Models
Abstract: Through alternative splicing, the same gene can be translated...
Josefine Tvermoes Meineche
BIOLOGICALLY INFORMED NEURAL NETWORKS FOR RISK STRATIFICATION AND CAUSAL INFERENCE IN CARDIOVASCULAR DISEASE AND DEMENTIA WITH A FOCUS ON GENDERED HEALTH DISCREPANCIES
Abstract: Atherosclerotic cardiovascular diseases (ASCVDs) and associated vascular dementia (VaD)...
Nils Grünefeld
Efficient Gradient-Based Uncertainty Quantification using Language Perturbation
Abstract: As data-driven decision making and automated systems achieve unprecedented...
Albert Kjøller Jacobsen
Geometric Approximate Bayesian Inference
Abstract: The proposed PhD project aims to improve traditional approximate...