Author

Oskar Kviman

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#machine learning Preprint Sep 2026

Variational Mixtures and Multi-Marginal Flow Matching: Advancing Statistical Inference with Biological Applications

In this thesis I develop methods for statistical inference when the distributions arising from complex biological systems are multi-modal, geometrically structured, and sometimes only defined up to a normalizing constant. I start from variational inference and, when analytic update equations are unavailable, move to bl...

Oskar Kviman · 0 citations

#machine learning Oct 2025

Multi-Marginal Flow Matching with Adversarially Learnt Interpolants

This paper proposes a novel flow matching method that overcomes the limitations of existing multi-marginal trajectory inference algorithms, using a GAN-inspired adversarial loss to fit neurally parametrised interpolant curves between source and target points such that the marginal distributions at intermediate time poi...

Oskar Kviman, Kirill Tamogashev, Nicola Branchini et al. · arXiv.org · 2 citations