Research theme 01

Bayesian inference

Turning noisy detector data into astrophysics: Bayesian inference, model selection, transdimensional inference, and neural posterior estimation.

17 papers

Papers

Papers on this theme 17

From my publication list, newest first.

Current group member

All publications

2026
Accurate and scalable inference for binary neutron stars in next-generation gravitational-wave detectors

Guttman (group member), Baker, Lasky & Thrane
- PRD 114, 063035
- arXiv:2606.14197
2026
BilbyFlow: user-friendly neural posterior estimation for gravitational-wave astronomy

Pinchbeck, Thrane, Balazs & Lasky
- Accepted to ApJS
- arXiv:2609.00766
2026
Fortifying gravitational-wave population inference with normalizing flows

Adamcewicz (group member), McDougall, Lasky & Thrane
- PRD 114, 043057
- arXiv:2606.14229
2026
Reconstructing Core-Collapse Supernova Gravitational-Wave Signals with Transdimensional Bayesian Inference

Chapman, Powell, Guttman (group member), Lee & Lasky
- Submitted to PRD
- arXiv:2608.05456
2026
Joint inference for gravitational-wave signal and noise glitch: Method and application

Cheung (group member), Udall, Davis, Lasky & Thrane
- Accepted to PRD
- arXiv:2607.09111
2025
Significant challenges for astrophysical inference with next-generation gravitational-wave observatories

Baker, Lasky, Thrane & Golomb
- PRD 112, 102004
- arXiv:2503.04073
2025
Modeling noise in gravitational-wave observatories with transdimensional models

Guttman (group member), Lasky & Thrane
- PRD 111, 063063
- arXiv:2501.03285
2025
Transdimensional Inference for Gravitational-wave Astronomy with Bilby

Tong, Guttman (group member), Clarke, Lasky et al.
- ApJS 276, 50
- arXiv:2404.04460
2023
GWCLOUD: A Searchable Repository for the Creation and Curation of Gravitational-wave Inference Results

Baker, Lasky, Thrane, Ashton, Cantos, Lakerink, Leslie, Poole & Reichardt
- ApJS 266, 33
- arXiv:2204.13267
2023
Generating transient noise artefacts in gravitational-wave detector data with generative adversarial networks

Powell, Sun, Gereb, Lasky & Dollmann
- CQG 40, 035006
- arXiv:2207.00207
2022
Gravitational-wave inference for eccentric binaries: the argument of periapsis

Clarke, Romero-Shaw, Lasky & Thrane
- MNRAS 517, 3778
- arXiv:2206.14006
2022
When models fail: An introduction to posterior predictive checks and model misspecification in gravitational-wave astronomy

Romero-Shaw, Thrane & Lasky
- PASA 39, e025
- arXiv:2202.05479

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2021
Bayesian Inference for Gravitational Waves from Binary Neutron Star Mergers in Third Generation Observatories

Smith, Borhanian, Sathyaprakash, Hernandez Vivanco, Lasky et al.
- PRL 127, 081102
- arXiv:2103.12274
2020
Bayesian inference for compact binary coalescences with BILBY: validation and application to the first LIGO-Virgo gravitational-wave transient catalogue

Romero-Shaw, Talbot, Biscoveanu, D'Emilio, Lasky et al.
- MNRAS 499, 3295
- arXiv:2006.00714
2020
Detection and parameter estimation of binary neutron star merger remnants

Easter, Ghonge, Lasky, Casey, Clark, Hernandez Vivanco & Chatziioannou
- PRD 102, 043011
- arXiv:2006.04396
2020
Memory effect or cosmic string? Classifying gravitational-wave bursts with Bayesian inference

Divakarla, Thrane, Lasky & Whiting
- PRD 102, 023010
- arXiv:1911.07998
2019
BILBY: A User-friendly Bayesian Inference Library for Gravitational-wave Astronomy

Ashton, Hübner, Lasky, Talbot et al.
- ApJS 241, 27
- arXiv:1811.02042