activity
20172026
most citedMLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge

65 citations · 287 across the 27 of their papers we have counts for

collaborators

32 papers

astro-ph.IM2026

The best of all worlds: gravitational-wave transient detection with multiple pipelines

Nikolas Moustakidis, Theofilos Moustakidis, Deep Chatterjee +2

The search for gravitational-wave transients (modeled and unmodeled) as performed by the LIGO-Virgo-KAGRA collaborations and the broader community typically involves multiple detec…

gr-qc2024★ 24 cited

New Gravitational Wave Discoveries Enabled by Machine Learning

Alexandra E. Koloniari, Evdokia C. Koursoumpa, Paraskevi Nousi +4

The detection of gravitational waves has revolutionized our understanding of the universe, offering unprecedented insights into its dynamics. A major goal of gravitational wave dat…

cs.CV2023

Deep Active Perception for Object Detection using Navigation Proposals

Stefanos Ginargiros, Nikolaos Passalis, Anastasios Tefas

Deep Learning (DL) has brought significant advances to robotics vision tasks. However, most existing DL methods have a major shortcoming, they rely on a static inference paradigm i…

q-fin.PM2023★ 1 cited

Leveraging Deep Learning and Online Source Sentiment for Financial Portfolio Management

Paraskevi Nousi, Loukia Avramelou, Georgios Rodinos +10

Financial portfolio management describes the task of distributing funds and conducting trading operations on a set of financial assets, such as stocks, index funds, foreign exchang…

cs.ET2023

Non-negative isomorphic neural networks for photonic neuromorphic accelerators

Manos Kirtas, Nikolaos Passalis, Nikolaos Pleros +1

Neuromorphic photonic accelerators are becoming increasingly popular, since they can significantly improve computation speed and energy efficiency, leading to femtojoule per MAC ef…

cs.LG2023★ 11 cited

Multiplicative update rules for accelerating deep learning training and increasing robustness

Manos Kirtas, Nikolaos Passalis, Anastasios Tefas

Even nowadays, where Deep Learning (DL) has achieved state-of-the-art performance in a wide range of research domains, accelerating training and building robust DL models remains a…