335 citations · 410 across the 6 of their papers we have counts for
9 papers
Data quality up to the third observing run of Advanced LIGO: Gravity Spy glitch classifications
J. Glanzer, S. Banagiri, S. B. Coughlin +10
Understanding the noise in gravitational-wave detectors is central to detecting and interpreting gravitational-wave signals. Glitches are transient, non-Gaussian noise features tha…
Discriminative Dimensionality Reduction using Deep Neural Networks for Clustering of LIGO Data
Sara Bahaadini, Yunan Wu, Scott Coughlin +2
In this paper, leveraging the capabilities of neural networks for modeling the non-linearities that exist in the data, we propose several models that can project data into a low di…
MTLB-STRUCT @PARSEME 2020: Capturing Unseen Multiword Expressions Using Multi-task Learning and Pre-trained Masked Language Models
Shiva Taslimipoor, Sara Bahaadini, Ekaterina Kochmar
This paper describes a semi-supervised system that jointly learns verbal multiword expressions (VMWEs) and dependency parse trees as an auxiliary task. The model benefits from pre-…
Leveraging Semi-Supervised Learning for Fairness using Neural Networks
Vahid Noroozi, Sara Bahaadini, Samira Sheikhi +2
There has been a growing concern about the fairness of decision-making systems based on machine learning. The shortage of labeled data has been always a challenging problem facing…
Semi-supervised Deep Representation Learning for Multi-View Problems
Vahid Noroozi, Sara Bahaadini, Lei Zheng +3
While neural networks for learning representation of multi-view data have been previously proposed as one of the state-of-the-art multi-view dimension reduction techniques, how to…
DIRECT: Deep Discriminative Embedding for Clustering of LIGO Data
Sara Bahaadini, Vahid Noroozi, Neda Rohani +3
In this paper, benefiting from the strong ability of deep neural network in estimating non-linear functions, we propose a discriminative embedding function to be used as a feature…
SEVEN: Deep Semi-supervised Verification Networks
Vahid Noroozi, Lei Zheng, Sara Bahaadini +2
Verification determines whether two samples belong to the same class or not, and has important applications such as face and fingerprint verification, where thousands or millions o…
Deep Multi-view Models for Glitch Classification
Sara Bahaadini, Neda Rohani, Scott Coughlin +3
Non-cosmic, non-Gaussian disturbances known as "glitches", show up in gravitational-wave data of the Advanced Laser Interferometer Gravitational-wave Observatory, or aLIGO. In this…
Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science
Michael Zevin, Scott Coughlin, Sara Bahaadini +15
(abridged for arXiv) With the first direct detection of gravitational waves, the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) has initiated a new field of as…