Alessandra Buonanno

According to our database, Alessandra Buonanno authored at least 6 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Real-time inference for binary neutron star mergers using machine learning.

Maximilian Dax, Stephen R. Green, Jonathan Gair, Nihar Gupte, Michael Pürrer, Vivien Raymond, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf

Nat., March, 2025

pySEOBNR: A software package for the next generation of effective-one-body multipolar waveform models.

Deyan P. Mihaylov, Serguei Ossokine, Alessandra Buonanno, Hector Estelles, Lorenzo Pompili, Michael Pürrer, Antoni Ramos-Buades

SoftwareX, 2025

2024

Real-time gravitational-wave inference for binary neutron stars using machine learning.

Maximilian Dax, Stephen R. Green, Jonathan Gair, Nihar Gupte, Michael Pürrer, Vivien Raymond, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf

CoRR, 2024

2022

Adapting to noise distribution shifts in flow-based gravitational-wave inference.

Jonas Wildberger, Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf

CoRR, 2022

Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference.

Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf

CoRR, 2022

2021

Real-time gravitational-wave science with neural posterior estimation.

Maximilian Dax, Stephen R. Green, Jonathan Gair, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf

CoRR, 2021