Szabolcs Márka

According to our database, Szabolcs Márka authored at least 7 papers between 2021 and 2023.

Collaborative distances:

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

2023

TpopT: Efficient Trainable Template Optimization on Low-Dimensional Manifolds.

Jingkai Yan, Shiyu Wang, Xinyu Rain Wei, Jimmy Wang, Zsuzsanna Márka, Szabolcs Márka, John Wright

CoRR, 2023

2022

Boosting the Efficiency of Parametric Detection with Hierarchical Neural Networks.

Jingkai Yan, Robert E. Colgan, John Wright, Zsuzsa Márka, Imre Bartos, Szabolcs Márka

CoRR, 2022

Quantum encoding is suitable for matched filtering.

Doga Veske, Cenk Tüysüz, Mirko Amico, Nicholas T. Bronn, Olivia T. Lanes, Zsuzsa Márka, Szabolcs Márka

CoRR, 2022

Detecting and Diagnosing Terrestrial Gravitational-Wave Mimics Through Feature Learning.

Robert E. Colgan, Zsuzsa Márka, Jingkai Yan, Imre Bartos, John N. Wright, Szabolcs Márka

CoRR, 2022

Architectural Optimization and Feature Learning for High-Dimensional Time Series Datasets.

Robert E. Colgan, Jingkai Yan, Zsuzsa Márka, Imre Bartos, Szabolcs Márka, John N. Wright

CoRR, 2022

2021

Enhancing gravitational-wave science with machine learning.

Elena Cuoco, Jade Powell, Marco Cavaglià, Kendall Ackley, Michal Bejger, Chayan Chatterjee, Michael Coughlin, Scott Coughlin, Paul Easter, Reed Essick, Hunter Gabbard, Timothy Gebhard, Shaon Ghosh, Leïla Haegel, Alberto Iess, David Keitel, Zsuzsa Márka, Szabolcs Márka, Filip Morawski, Tri Nguyen, Rich Ormiston, Michael Pürrer, Massimiliano Razzano, Kai Staats, Gabriele Vajente, Daniel Williams

Mach. Learn. Sci. Technol., 2021

Generalized Approach to Matched Filtering using Neural Networks.

Jingkai Yan, Mariam Avagyan, Robert E. Colgan, Doga Veske, Imre Bartos, John N. Wright, Zsuzsa Márka, Szabolcs Márka

CoRR, 2021