13 citations · 14 across the 8 of their papers we have counts for
5 papers · 1 filter
SlotFlow: Amortized Trans-Dimensional Inference with Slot-Based Normalizing Flows
Niklas Houba, Giovanni Giarda, Lorenzo Speri
Inferring the number of distinct components contributing to an observation, while simultaneously estimating their parameters, remains a long-standing challenge across signal proces…
Deep source separation of overlapping gravitational-wave signals and non-stationary noise artifacts
Niklas Houba
The Laser Interferometer Space Antenna (LISA) will observe gravitational waves in the millihertz frequency band, detecting signals from a vast number of astrophysical sources embed…
Robust Bayesian inference with gapped LISA data using all-in-one TDI-
Niklas Houba, Jean-Baptiste Bayle, Michele Vallisneri
The Laser Interferometer Space Antenna (LISA), an ESA L-class mission, is designed to detect gravitational waves in the millihertz frequency band, with operations expected to begin…
Detection and Prediction of Future Massive Black Hole Mergers with Machine Learning and Truncated Waveforms
Niklas Houba, Stefan H. Strub, Luigi Ferraioli +1
We present a novel machine learning framework tailored to detect massive black hole binaries observed by spaceborne gravitational wave detectors like the Laser Interferometer Space…
Detection and Mitigation of Glitches in LISA Data: A Machine Learning Approach
Niklas Houba, Luigi Ferraioli, Domenico Giardini
The proposed Laser Interferometer Space Antenna (LISA) mission is tasked with the detection and characterization of gravitational waves from various sources in the universe. This e…