Non-Astrophysical Transients in LIGO Detectors: Help With Machine Learning
Institute for Pure & Applied Mathematics (IPAM) via YouTube
Pass the PMP® Exam on Your First Try — Expert-Led Training
Master Production-Ready Machine Learning, Step by Step
Overview
Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates
Explore machine learning techniques for diagnosing non-astrophysical transients in LIGO detectors in this 34-minute conference talk by Gabriela González from Louisiana State University. Presented at IPAM's Workshop IV: Big Data in Multi-Messenger Astrophysics, the talk delves into examples of how advanced algorithms can aid in identifying and understanding anomalous signals that are not of cosmic origin. Gain insights into the challenges faced by gravitational wave researchers and the innovative solutions being developed to improve data analysis in the field of multi-messenger astrophysics.
Syllabus
Gabriela Gonzalez - Non-astrophysical transients in LIGO detectors: help with machine learning
Taught by
Institute for Pure & Applied Mathematics (IPAM)