2 papers
astro-ph.IM2026
Sample-efficient non-Gaussian noise reduction in gravitational wave data via learnable wavelets
Arush Pimpalkar, Digvijay Wadekar, Mark Ho-Yeuk Cheung +1
We introduce , a wavelet-based neural network architecture to identify and reduce non-Gaussian noise in gravitational wave data. Traditionally, convolutional n…
gr-qc2025
Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation
Digvijay Wadekar, Arush Pimpalkar, Mark Ho-Yeuk Cheung +9
We introduce a machine learning (ML) framework called for improving the sensitivity of gravitational wave search pipelines. Typically, search pipelines only use a s…