Machine Learning for H? Emitters Classification
Stellar Dating Using Chemical Clocks and Bayesian Inference
Detection of Quasi-Periodic Oscillations in Time Series of a Cataclysmic Variable Using Support Vector Machine
Dust Extinction from Random Forest Regression of Interstellar Lines
QSOs Selection in Highly Unbalanced Photometric Datasets: The "Michelangelo" Reverse-Selection Method
Radio Galaxy Detection Prediction with Ensemble Machine Learning
A Machine Learning Suite to Halo-Galaxy Connection
New Applications of Graph Neural Networks in Cosmology
Detection of Point Sources in Maps of the Temperature Anisotropies of the Cosmic Microwave Background
Reconstruction and Particle Identification with CYGNO Experiment
Event Reconstruction for Neutrino Telescopes
Classification of Evolved Stars with (Unsupervised) Machine Learning Post Proceedings
Patterns in the Chaos: An Unsupervised View of Galactic Supernova Remnants
Clustering of Galaxy Spectra: An Unsupervised Approach with Fisher-EM
Unsupervised Classification Reveals New Evolutionary Pathways
In Search of the Peculiar: An Unsupervised Approach to Anomaly Detection in the Transient Universe
Classifying Gamma-Ray Burst X-Ray Afterglows with a Variational Autoencoder
Reconstructing Blended Galaxies with Machine Learning
Time Domain Astroinformatics
A Convolutional Neural Network to Characterise the Internal Structure of Stars
Finding Stellar Flares with Recurrent Deep Neural Networks
Planetary Markers in Stellar Spectra: Jupiter-Host Star Classification
Using Convolutional Neural Networks to Detect and Confirm Exoplanets
Machine Learning Applied to X-Ray Spectra: Separating Stars from Active Galactic Nuclei
Classification of System Variability Using A CNN
Deep Learning Processing and Analysis of Mock Astrophysical Observations
Deep Neural Networks for Source Detection in Radio Astronomical Maps
Radio Image Segmentation with Autoencoders
Citizen Science and Machine Learning: Towards a Robust Large-Scale Automatic Classification in Astronomy
Background Estimation in Fermi Gamma-Ray Burst Monitor Lightcurves Through a Neural Network
Machine Learning Investigations for LSST: Strong Lens Mass Modeling and Photometric Redshift Estimation
Multi-Band Photometry and Photometric Redshifts from Astronomical Images
Inference of Galaxy Clusters Mass Radial Profiles from Compton-? Maps with Deep Learning Technique
Deep Learning 21cm Lightcones in 3D
ConvNets for Enhanced Background Discrimination in the Diffuse Supernova Neutrino-Background (DSNB) Search
Deep Neural Networks for Single-Line Event Direction Reconstruction in ANTARES
Cats Vs Dogs, Photons Vs Hadrons
Events Classification in MAGIC Through Convolutional Neural Network Trained with Images of Observed Gamma-Ray Events
Federated Learning Meets HPC and Cloud
Integration and Deployment of Model Serving Framework at Production Scale
Predictive Maintenance for Array of Cherenkov Telescopes.