Overlapping Galactic binaries complicate instrumental-noise estimation for space-based gravitational-wave detectors. This study combines population-level generative modeling, convolutional foreground prediction, and spectral-covariance inference for …
Transient glitches can distort Bayesian inference for massive black-hole binaries. This preprint combines time-frequency representations, contrastive learning, and conditional normalizing flows to infer source parameters from contaminated Taiji data. …
Extreme-mass-ratio inspirals have complex waveforms and difficult posterior structure. This study applies flow matching and continuous normalizing flows to accelerate Bayesian parameter estimation. Simulated analyses compare learned posteriors with …
The 21-cm forest can probe dark-matter properties and the heating history of the early intergalactic medium. This study uses normalizing flows for simulated-data augmentation and likelihood-free parameter inference. Tests with simulated radio …