A Deep Learning Powered Numerical Relativity Surrogate for Binary Black Hole Waveforms

Documenti analoghi

• An autoencoder-based surrogate waveform model for quasi-circular binary-black-hole mergers
  di: Theodoropoulos, Anastasios, et al.
  Pubblicazione: (2026)
• Comparison of neural network architectures for feature extraction from binary black hole merger waveforms
  di: Freitas, Osvaldo Gramaxo, et al.
  Pubblicazione: (2023)
• Deep-Learning Classification and Parameter Inference of Rotational Core-Collapse Supernovae
  di: Nunes, Solange, et al.
  Pubblicazione: (2024)
• Parameter estimation of microlensed gravitational waves with Conditional Variational Autoencoders
  di: Bada-Nerin, Roberto, et al.
  Pubblicazione: (2024)
• VIGILant: an automatic classification pipeline for glitches in the Virgo detector
  di: Fernandes, Tiago, et al.
  Pubblicazione: (2026)