Oskar Kviman

Personal webpage

I am a PhD student working in the Lagergren Lab. My research interests are in Bayesian phylogenetics and probabilistic machine learning in general. From a machine learning perspective, my recent and current works involve, e.g., variational inference, variational auto-encoders, importance sampling, sequential Monte Carlo methods and Monte Carlo objective functions. In phylogenetics, I research variational inference-based phylogenetics, tree sampling methods and joint inference of gene and species trees.

Articles

• Learning with MISELBO: The Mixture Cookbook, arxiv 2022
• VaiPhy: a Variational Inference Based Algorithm for Phylogeny, NeurIPS 2022
•  Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations, AISTATS 2o22

Teaching

• Statistical Methods in Applied Computer Science (DD2447)
• Machine Learning, Advanced Course (DD2434)