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Training Strategies for Deep Learning Gravitational-Wave Searches
v1v2 (latest)

Training Strategies for Deep Learning Gravitational-Wave Searches

7 June 2021
Marlin B. Schäfer
O. Zelenka
A. Nitz
F. Ohme
Bernd Brügmann
ArXiv (abs)PDFHTML

Papers citing "Training Strategies for Deep Learning Gravitational-Wave Searches"

4 / 4 papers shown
Title
Learning and Interpreting Gravitational-Wave Features from CNNs with a Random Forest Approach
Learning and Interpreting Gravitational-Wave Features from CNNs with a Random Forest Approach
Jun Tian
He Wang
Jibo He
Yu Pan
Shuo Cao
Qingquan Jiang
41
0
0
26 May 2025
DeepSNR: A deep learning foundation for offline gravitational wave
  detection
DeepSNR: A deep learning foundation for offline gravitational wave detection
Michael Andrews
M. Paulini
Luke Sellers
Alexey Bobrick
Gianni Martire
Haydn Vestal
OffRL
41
6
0
11 Jul 2022
Inference-optimized AI and high performance computing for gravitational
  wave detection at scale
Inference-optimized AI and high performance computing for gravitational wave detection at scale
Pranshu Chaturvedi
Asad Khan
Minyang Tian
Eliu A. Huerta
Huihuo Zheng
72
28
0
26 Jan 2022
AI and extreme scale computing to learn and infer the physics of higher
  order gravitational wave modes of quasi-circular, spinning, non-precessing
  binary black hole mergers
AI and extreme scale computing to learn and infer the physics of higher order gravitational wave modes of quasi-circular, spinning, non-precessing binary black hole mergers
Asad Khan
E. A. H. abd
Prayush Kumar
67
5
0
13 Dec 2021
1