Jonathan Gair

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 8

Top Topics

Bayesian Inference

Machine Learning

Importance Sampling

Top Venues

Mach. Learn. Sci. Technol.

Publications

Maximilian Dax, Stephen R. Green, Jonathan Gair, Nihar Gupte, Michael Pürrer, Vivien Raymond, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
Real-time gravitational-wave inference for binary neutron stars using machine learning. CoRR (2024)
Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference. CoRR (2022)
Jonas Wildberger, Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
Adapting to noise distribution shifts in flow-based gravitational-wave inference. CoRR (2022)
Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke
Group equivariant neural posterior estimation. ICLR (2022)
Maximilian Dax, Stephen R. Green, Jonathan Gair, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
Real-time gravitational-wave science with neural posterior estimation. CoRR (2021)
Stephen R. Green, Jonathan Gair
Complete parameter inference for GW150914 using deep learning. Mach. Learn. Sci. Technol. 2 (3) (2021)
Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke
Group equivariant neural posterior estimation. CoRR (2021)
Stephen R. Green, Christine Simpson, Jonathan Gair
Gravitational-wave parameter estimation with autoregressive neural network flows. CoRR (2020)