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20242026
most citedA machine-learning pipeline for real-time detection of gravitational waves from compact binary coalescences

3 citations · 4 across the 9 of their papers we have counts for

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5 papers · 1 filter

gr-qc2024

A Neural Network-Based Search for Unmodeled Transients in LIGO-Virgo-KAGRA's Third Observing Run

Ryan Raikman, Eric A. Moreno, Katya Govorkova +13

This paper presents the results of a Neural Network (NN)-based search for short-duration gravitational-wave transients in data from the third observing run of LIGO, Virgo, and KAGR…

cs.LG2024

Low Latency Transformer Inference on FPGAs for Physics Applications with hls4ml

Zhixing Jiang, Dennis Yin, Yihui Chen +7

This study presents an efficient implementation of transformer architectures in Field-Programmable Gate Arrays(FPGAs) using hls4ml. We demonstrate the strategy for implementing the…

gr-qc2024

Rapid Likelihood Free Inference of Compact Binary Coalescences using Accelerated Hardware

Deep Chatterjee, Ethan Marx, William Benoit +12

We report a gravitational-wave parameter estimation algorithm, AMPLFI, based on likelihood-free inference using normalizing flows. The focus of AMPLFI is to perform real-time param…

gr-qc2024★ 3 cited

A machine-learning pipeline for real-time detection of gravitational waves from compact binary coalescences

Ethan Marx, William Benoit, Alec Gunny +12

The promise of multi-messenger astronomy relies on the rapid detection of gravitational waves at very low latencies ((1\,s)) in order to maximize the amount of time av…

cs.LG2024★ 1 cited

Ultra Fast Transformers on FPGAs for Particle Physics Experiments

Zhixing Jiang, Dennis Yin, Elham E Khoda +6

This work introduces a highly efficient implementation of the transformer architecture on a Field-Programmable Gate Array (FPGA) by using the \texttt{hls4ml} tool. Given the demons…