65 citations · 153 across the 11 of their papers we have counts for
11 papers
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…
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…
Deep Learning for Energy Time-Series Analysis and Forecasting
Maria Tzelepi, Charalampos Symeonidis, Paraskevi Nousi +5
Energy time-series analysis describes the process of analyzing past energy observations and possibly external factors so as to predict the future. Different tasks are involved in t…
Variational Voxel Pseudo Image Tracking
Illia Oleksiienko, Paraskevi Nousi, Nikolaos Passalis +2
Uncertainty estimation is an important task for critical problems, such as robotics and autonomous driving, because it allows creating statistically better perception models and si…
Deep Residual Networks for Gravitational Wave Detection
Paraskevi Nousi, Alexandra E. Koloniari, Nikolaos Passalis +3
Traditionally, gravitational waves are detected with techniques such as matched filtering or unmodeled searches based on wavelets. However, in the case of generic black hole binari…
A Novel Dataset for Evaluating and Alleviating Domain Shift for Human Detection in Agricultural Fields
Paraskevi Nousi, Emmanouil Mpampis, Nikolaos Passalis +2
In this paper we evaluate the impact of domain shift on human detection models trained on well known object detection datasets when deployed on data outside the distribution of the…
MLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge
Marlin B. Schäfer, Ondřej Zelenka, Alexander H. Nitz +20
We present the results of the first Machine Learning Gravitational-Wave Search Mock Data Challenge (MLGWSC-1). For this challenge, participating groups had to identify gravitationa…
VPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images
Illia Oleksiienko, Paraskevi Nousi, Nikolaos Passalis +2
In this paper, we propose a novel voxel-based 3D single object tracking (3D SOT) method called Voxel Pseudo Image Tracking (VPIT). VPIT is the first method that uses voxel pseudo i…
Deep Residual Error and Bag-of-Tricks Learning for Gravitational Wave Surrogate Modeling
Styliani-Christina Fragkouli, Paraskevi Nousi, Nikolaos Passalis +3
Deep learning methods have been employed in gravitational-wave astronomy to accelerate the construction of surrogate waveforms for the inspiral of spin-aligned black hole binaries,…
Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling
Paraskevi Nousi, Styliani-Christina Fragkouli, Nikolaos Passalis +5
Recently, artificial neural networks have been gaining momentum in the field of gravitational wave astronomy, for example in surrogate modelling of computationally expensive wavefo…
Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data
Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis +5
Forecasting the movements of stock prices is one the most challenging problems in financial markets analysis. In this paper, we use Machine Learning (ML) algorithms for the predict…