3 papers
cs.LG2025
Incorporating Expert Knowledge into Bayesian Causal Discovery of Mixtures of Directed Acyclic Graphs
Zachris Björkman, Jorge Loría, Sophie Wharrie +1
Bayesian causal discovery benefits from prior information elicited from domain experts, and in heterogeneous domains any prior knowledge would be badly needed. However, so far prio…
cs.LG2023
Bayesian Meta-Learning for Improving Generalizability of Health Prediction Models With Similar Causal Mechanisms
Sophie Wharrie, Lisa Eick, Lotta Mäkinen +3
Machine learning strategies like multi-task learning, meta-learning, and transfer learning enable efficient adaptation of machine learning models to specific applications in health…
stat.AP2023
Characterizing personalized effects of family information on disease risk using graph representation learning
Sophie Wharrie, Zhiyu Yang, Andrea Ganna +1
Family history is considered a risk factor for many diseases because it implicitly captures shared genetic, environmental and lifestyle factors. Finland's nationwide electronic hea…