Enhancing Gravitational-Wave Detection: A Machine Learning Pipeline Combination Approach with Robust Uncertainty Quantification

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@article{1990448a15b941f78988fe3d2213bd9a,

title = "Enhancing Gravitational-Wave Detection: A Machine Learning Pipeline Combination Approach with Robust Uncertainty Quantification",

author = "Gregory Ashton and Ann-Kristin Malz and Nicolo Colombo",

year = "2026",

month = jan,

day = "8",

doi = "10.1103/yfb3-fgf2",

language = "English",

volume = "136",

journal = "Physical Review Letters",

issn = "1079-7114",

publisher = "American Physical Society",

number = "1",

}

TY - JOUR

T1 - Enhancing Gravitational-Wave Detection

T2 - A Machine Learning Pipeline Combination Approach with Robust Uncertainty Quantification

AU - Ashton, Gregory

AU - Malz, Ann-Kristin

AU - Colombo, Nicolo

PY - 2026/1/8

Y1 - 2026/1/8

U2 - 10.1103/yfb3-fgf2

DO - 10.1103/yfb3-fgf2

M3 - Letter

SN - 1079-7114

VL - 136

JO - Physical Review Letters

JF - Physical Review Letters

IS - 1

M1 - 011402

ER -