Author

Nicola Branchini

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#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 points are close to the observed distributions.

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