Author

Michal Bejger

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Preprint Sep 2026

Set Transformer inference of the neutron star equation of state from stellar observations

We develop a permutation-invariant Set Transformer to reconstruct the equation of state (EoS) of dense matter from variable-size, unordered sets of neutron star (NS) observations. The model takes stellar masses together with radii, tidal deformabilities, or both, and predicts either the pressure $P(n)$ or the sound spe...

M. Ferreira, Valéria Carvalho, Michal Bejger et al. · 1 citation

#machine learning Preprint Sep 2026

Deterministic denoising of long-duration gravitational-wave signal candidates with $\alpha$-(de)blending

The deterministic machine-learning method for denoising candidate signals from all-sky searches for continuous gravitational waves from rotating neutron stars recovers the correct sky-position-dependent pattern for signal-to-noise ratios, demonstrating that deterministic diffusion-based denoising may serve as a consist...

P. Figura, Michal Bejger · 0 citations