Machine learning for astrophysics proceedings of the ML4Astro International Conference 30 May-1 June 2022 /
This book reviews the state of the art in the exploitation of machine learning techniques for the astrophysics community and gives the reader a complete overview of the field. The contributed chapters allow the reader to easily digest the material through balanced theoretical and numerical methods a...
| Corporate Authors: | International Conference on Machine Learning for Astrophysics Catania, Italy ; Online) |
|---|---|
| Other Authors: | International Conference on Machine Learning for Astrophysics, Bufano, Filomena,, Riggi, Simone,, Sciacca, Eva,, Schilliro, Francesco,, SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer,
2023.
|
| Physical Description: |
1 online resource (180 pages) : illustrations (black and white, and color). |
| Series: |
Astrophysics and space science proceedings ;
v. 60. |
| Subjects: |
Table of Contents:
- 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.