Stephen R. Green

According to our database, Stephen R. Green authored at least 8 papers between 2020 and 2023.

Collaborative distances:

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

2023

Flow Matching for Scalable Simulation-Based Inference.

Jonas Wildberger, Maximilian Dax, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Using machine learning to parametrize postmerger signals from binary neutron stars.

Tim Whittaker, William E. East, Stephen R. Green, Luis Lehner, Huan Yang

CoRR, 2022

Group equivariant neural posterior estimation.

Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Complete parameter inference for GW150914 using deep learning.

Stephen R. Green, Jonathan Gair

Mach. Learn. Sci. Technol., September, 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

2020

Gravitational-wave parameter estimation with autoregressive neural network flows.

Stephen R. Green, Christine Simpson, Jonathan Gair

CoRR, 2020