4 citations · 11 across the 5 of their papers we have counts for
5 papers
Improved Variational Bayesian Phylogenetic Inference using Mixtures
Oskar Kviman, Ricky Molén, Jens Lagergren
We present VBPI-Mixtures, an algorithm designed to enhance the accuracy of phylogenetic posterior distributions, particularly for tree-topology and branch-length approximations. De…
Statistical Distance Based Deterministic Offspring Selection in SMC Methods
Oskar Kviman, Hazal Koptagel, Harald Melin +1
Over the years, sequential Monte Carlo (SMC) and, equivalently, particle filter (PF) theory has gained substantial attention from researchers. However, the performance of the resam…
Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders
Oskar Kviman, Ricky Molén, Alexandra Hotti +3
In this paper, we show how the mixture components cooperate when they jointly adapt to maximize the ELBO. We build upon recent advances in the multiple and adaptive importance samp…
VaiPhy: a Variational Inference Based Algorithm for Phylogeny
Hazal Koptagel, Oskar Kviman, Harald Melin +2
Phylogenetics is a classical methodology in computational biology that today has become highly relevant for medical investigation of single-cell data, e.g., in the context of cance…
Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations
Oskar Kviman, Harald Melin, Hazal Koptagel +2
In variational inference (VI), the marginal log-likelihood is estimated using the standard evidence lower bound (ELBO), or improved versions as the importance weighted ELBO (IWELBO…