Sarah Caudill

According to our database, Sarah Caudill authored at least 6 papers between 2018 and 2025.

Collaborative distances:

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

2025

DeepExtractor: Time-domain reconstruction of signals and glitches in gravitational wave data with deep learning.

Tom Dooney, Harsh Narola, Stefano Bromuri, R. Lyana Curier, Chris Van Den Broeck, Sarah Caudill, Daniel Stanley Tan

CoRR, January, 2025

Improving early detection of gravitational waves from binary neutron stars using CNNs and FPGAs.

Ana Martins, Melissa Lopez, Gregory Baltus, Quirijn Meijer, Marc van der Sluys, Chris Van Den Broeck, Sarah Caudill

Mach. Learn. Sci. Technol., 2025

2021

GstLAL: A software framework for gravitational wave discovery.

Kipp Cannon, Sarah Caudill, Chiwai Chan, Bryce Cousins, Jolien D. E. Creighton, Becca Ewing, Heather Fong, Patrick Godwin, Chad Hanna, Shaun Hooper, Rachael Huxford, Ryan Magee, Duncan Meacher, Cody Messick, Soichiro Morisaki, Debnandini Mukherjee, Hiroaki Ohta, Alexander Pace, Stephen Privitera, Iris de Ruiter, Surabhi Sachdev, Leo Singer, Divya Singh, Ron Tapia, Leo Tsukada, Daichi Tsuna, Takuya Tsutsui, Koh Ueno, Aaron Viets, Leslie Wade, Madeline Wade

SoftwareX, 2021

Swift sky localization of gravitational waves using deep learning seeded importance sampling.

Alex Kolmus, Grégory Baltus, Justin Janquart, Twan van Laarhoven, Sarah Caudill, Tom Heskes

CoRR, 2021

Detecting the early inspiral of a gravitational-wave signal with convolutional neural networks.

Grégory Baltus, Jean-René Cudell, Justin Janquart, Melissa Lopez, Sarah Caudill, Amit Reza

Proceedings of the 18th International Conference on Content-Based Multimedia Indexing, 2021

2018

Techniques for gravitational-wave detection of compact binary coalescence.

Sarah Caudill

Proceedings of the 26th European Signal Processing Conference, 2018