BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Costantino Pacilio "Gravitational-wave data analysis with machine 
 learning and deep learning"
DTSTART:20260128T113000Z
DTEND:20260128T130000Z
DTSTAMP:20260506T224800Z
UID:indico-event-50507@agenda.infn.it
CONTACT:costantino.pacilio@unimib.it
DESCRIPTION:Gravitational-wave astronomy enables precision studies of comp
 act binary systems and provides powerful tests of General Relativity. Blac
 k-hole spectroscopy—the detection of gravitational-wave emission spectra
  from black-hole ringdowns—offers a particularly clean framework for tes
 ting gravity theories against well-defined predictions. However\, accurate
  waveform modeling and efficient parameter estimation are essential to ext
 ract both astrophysical and fundamental physics insights from the data. In
  this talk\, I will present my recent works in gravitational waveform mode
 ling and inference\, with a focus on black hole ringdowns\, and highlighti
 ng the role of machine learning and deep learning techniques. In particula
 r\, I will discuss the promises and challenges of using Gaussian Process R
 egression for waveform modeling and hierarchical inference\, and simulatio
 n-based inference for parameter estimation.\n\nhttps://agenda.infn.it/even
 t/50507/
LOCATION:Sala Cortini (Fermi building) (La Sapienza)
URL:https://agenda.infn.it/event/50507/
END:VEVENT
END:VCALENDAR