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The Detection, Extraction and Parameter Estimation of Extreme-Mass-Ratio Inspirals with Deep Learning

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals (EMRIs). This endeavor presents a significant challenge due to the complex and lengthy EMRI signals, further compounded by …

引力波探测与AI技术:揭示宇宙奥秘的新手段

2023年“第二届机器学习在天文学中的应用”研讨会. https://machinelearning2023.casconf.cn/

Detecting Extreme-Mass-Ratio Inspirals for Space-Borne Detectors with Deep Learning

Deep learning approach for EMRI detection achieving 94.2% TPR at 1% FPR, demonstrating the potential for efficient signal detection in space-based gravitational wave detectors.

GW Data Analysis & Deep Learning III

引力波暑期学校 Summer School on Gravitational Waves. Website

GW Data Analysis & Deep Learning II

引力波暑期学校 Summer School on Gravitational Waves. Website

GW Data Analysis & Machine Learning I

引力波暑期学校 Summer School on Gravitational Waves. Website

Gravitational Wave Detection and AI Technology: New Methods for Unveiling the Mysteries of the Universe

量子宇宙理论物理研究中心研讨会.

Rapid search for massive black hole binary coalescences using deep learning

Deep learning method for rapid detection of massive black hole binary coalescences in LISA data, achieving high sensitivity with no false alarms while processing 1-year data in seconds.

Clearing the Path to Discovery: Detecting and Denoising Gravitational Waves with Deep Learning

中国物理学会引力与相对论天体物理分会“2023年学术年会”. Website: http://cqutp.org/conferences/gr23/index.php

基于人工智能技术的引力波数据分析前沿

国家天文数据中心·天文信息学与虚拟天文台 2022 年学术年会. Website: https://nadc.china-vo.org/events/cvo2022/