Real-Time Gravitational-Wave Parameter Estimation Using Machine Learning

Real-Time Gravitational-Wave Parameter Estimation Using Machine Learning

Institute for Pure & Applied Mathematics (IPAM) via YouTube Direct link

Amortized inference

10 of 14

10 of 14

Amortized inference

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Real-Time Gravitational-Wave Parameter Estimation Using Machine Learning

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  1. 1 Introduction to parameter estimation
  2. 2 Sampling
  3. 3 Challenges
  4. 4 Simulation-based inference
  5. 5 Normalizing flow
  6. 6 Simulation-based training
  7. 7 Embedding network
  8. 8 Group equivariant neural posterior estimation
  9. 9 Importance of method validation
  10. 10 Amortized inference
  11. 11 Quantitative comparison vs standard sampler
  12. 12 Summary comparison
  13. 13 Conclusions
  14. 14 Outlook

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