| G2500012-v1 |
GWSkyNet-Multi II: An updated model for rapidly classifying LVK candidate alerts in O4 |
Nayyer Raza et al. |
Detector Characterization
Data Analysis
Machine Learning
GW source predictions
|
06 Jan 2025 |
| G2401339-v1 |
Modeling Gravitational-wave (GW) waveforms based on Machine learning (ML) |
Kexuan Wu |
Machine Learning
|
25 Jun 2024 |
| G2401326-v6 |
UBC/TRIUMF update for GWANW 2024 |
Jess McIver |
Data quality / vetoes
Core Optics
Computing/archiving
Calibration
Continuous Wave
Astrophysics / Multi-messenger
Detector
Compact Binaries
Detector Characterization
Data analysis software
Data Analysis
Machine Learning
|
25 Jun 2024 |
| P2300288-v3 |
Rapid neutron star equation of state inference with Normalising Flows |
Jordan McGinn et al. |
Astrophysics / Multi-messenger
Machine Learning
Compact Binaries
|
18 Apr 2024 |
| T2300288-v1 |
Implementing Nonlinear Control in a Classical Experiment to Reduce Measurement Noise |
Andrei Diaconu et al. |
Machine Learning
State Control and Monitoring
|
03 Apr 2024 |
| T2300219-v1 |
Identifying Correlations in Precessing Gravitational-Wave Signals with Machine Learning |
Karen Kang et al. |
Compact Binaries
Data Analysis
Machine Learning
|
03 Jan 2024 |
| T2300147-v2 |
LIGO Seismic State Characterization using Machine Learning Techniques |
Isaac Kelly et al. |
State Control and Monitoring
Machine Learning
|
30 Oct 2023 |
| G2301235-v2 |
O-LIGO Update for GWANW 2023 |
Benjamin Farr et al. |
Compact Binaries
Detector Characterization
Data analysis software
Machine Learning
Astrophysics / Multi-messenger
|
28 Jun 2023 |
| G2301233-v2 |
UBC/TRIUMF update for GWANW |
Jess McIver |
Data Analysis
Machine Learning
Detector Characterization
Compact Binaries
Data analysis software
Astrophysics / Multi-messenger
Detector
Continuous Wave
Meeting
Calibration
|
27 Jun 2023 |
| T2200196-v1 |
Developing Deep Learning Solutions for Lock Acquisition |
Peter Ma et al. |
Commissioning
Sensing and Control
Machine Learning
|
10 Mar 2023 |
| T2200207-v3 |
Identifying Witnesses to LIGO Glitches Using Auxiliary Channels |
Luis Bariuan et al. |
Machine Learning
|
20 Sep 2022 |
| T2000181-v3 |
Nonlinear Regression of Technical Noise in LIGO with Machine Learning |
Rana Adhikari et al. |
Basic R&D
Machine Learning
Detector Characterization
|
25 Oct 2021 |
| T2000390-v4 |
Machine Learning Applications in Gravitational Wave Detection to Reduce Noise |
Nadezhda Dimitrova et al. |
Data quality / vetoes
Data Analysis
Machine Learning
Detector Characterization
|
02 Dec 2020 |
| G1901483-v6 |
Source-classification and source-properties computation in low-latency |
Shaon Ghosh |
Machine Learning
Compact Binaries
Astrophysics / Multi-messenger
GW source predictions
|
15 Aug 2019 |
| T1800282-v1 |
Utilizing Machine Learning to Improve Searches for LIGO Sources |
Sarah McCarthy et al. |
Detector Characterization
Compact Binaries
Machine Learning
|
30 Mar 2019 |
| T1800288-v4 |
Sub-Classification of Blip Glitches Using Q-Transforms and Convolutional Neural Networks with GravitySpy |
Melissa Kohl et al. |
Detector Characterization
Data analysis software
Machine Learning
Data quality / vetoes
|
30 Mar 2019 |
| L1900080-v1 |
GW Cloud: Executive Summary |
Paul Lasky et al. |
GW source predictions
Computing/archiving
Data analysis software
Compact Binaries
Machine Learning
|
26 Feb 2019 |