CNN

Rapid search for massive black hole binary coalescences using deep learning

Applies deep learning to searches for massive-black-hole-binary coalescences in simulated LISA data. The analysis evaluates detection latency, false alarms, and generalization across waveform families and detector configurations, with the aim of …

机器学习在引力波数据处理中的应用

东北大学引力波宇宙学与射电天文学研究中心青年学者研讨会 - 特邀报告

Machine Learning in Gravitational Wave Data Analysis

Poster: https://ictp-ap.org/event/60

Deep neural networks & Gravitational-wave signal recognization

Exploring Gravitational-Wave Detection & Parameter Inference using Deep Learning

Ensemble of deep convolutional neural networks for real-time gravitational wave signal recognition

Studies an ensemble of convolutional neural networks for low-latency gravitational-wave recognition. Independent classifiers are combined to improve detection performance, with tests that assess the method on simulated signals and observational …

Exploring Gravitational-Wave Detection and Parameter Inference using Deep Learning

Exploring Gravitational-Wave Detection and Parameter Inference using Deep Learning

Gravitational-wave Signal Recognition of LIGO Data by Deep Learning

Gravitational-wave Signal Recognition of LIGO Data by Deep Learning