Gravitational-wave parameter estimation with machine-learning generated surrogate waveforms
The worldwide network of gravitational-wave detectors have detected more than 350 binary coalescence events till date. Future third-generation detectors, like Einstein telescope, are expected to detect orders-of-magnitude more signals from sources with more complicated characteristics, including eccentric orbits and high-mass ratio binaries. It is well-established that the computational cost of parameter estimation for signals from these kinds of sources will be extremely high. In particular, the process could be sped-up if generating theoretical waveform predictions, used for likelihood calcu
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- FuzzySimilar title/name (fuzzy) · 66%stefan-jansen/machine-learning-for-trading →
“Fuzzy title match (0.78): “Gravitational-wave parameter estimation with machine-learnin” ≈ “stefan-jansen/machine-learning-for-trading””
- FuzzySimilar title/name (fuzzy) · 66%DataTalksClub/machine-learning-zoomcamp →
“Fuzzy title match (0.78): “Gravitational-wave parameter estimation with machine-learnin” ≈ “DataTalksClub/machine-learning-zoomcamp””
- FuzzySimilar title/name (fuzzy) · 59%EthicalML/awesome-production-machine-learning →
“Fuzzy title match (0.73): “Gravitational-wave parameter estimation with machine-learnin” ≈ “EthicalML/awesome-production-machine-learning””
- FuzzySimilar title/name (fuzzy) · 59%rasbt/python-machine-learning-book →
“Fuzzy title match (0.73): “Gravitational-wave parameter estimation with machine-learnin” ≈ “rasbt/python-machine-learning-book””
- FuzzySimilar title/name (fuzzy) · 59%aymericdamien/TopDeepLearning →
“Fuzzy title match (0.73): “Gravitational-wave parameter estimation with machine-learnin” ≈ “aymericdamien/TopDeepLearning””
- LinkedLinked via arxiv author · 85%Suyog Garg →
“Gravitational-wave parameter estimation with machine-learning generated surrogate waveforms”
- LinkedLinked via arxiv author · 85%Kipp Cannon →
“Gravitational-wave parameter estimation with machine-learning generated surrogate waveforms”