Bring together researchers actively involved in the fields of machine learning applications to astrophysics use cases is the aim of the International Conference on Machine Learning for Astrophysics - ML4Astro.
In the view of the forthcoming Big Data era for the astronomy community, the conference focuses on challenges coming from the application of ML/DL methods to open problems in astrophysics: novel AI techniques will be presented and joint discussions on their use with observational data will be fostered. A special session on the Square Kilometre Array and its precursors/pathfinders is foreseen.
Participants are invited to submit an abstract for an Oral Presentation or a Poster Presentation on the topics of interest for the conference. Conference Proceedings in Springer book series ASSP are foreseen both for Oral and Poster accepted contributions.
Topics:
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Supervised/Unsupervised/Semi-supervised Learning
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Deep learning
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Active Learning
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Image segmentation, object detection and classification
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Anomaly discovery
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Data preparation, generation and augmentation
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Time series analysis, transients
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Classification and regression
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Data mining
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Software tools and services for machine learning
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Computing infrastructures and devices for Artificial Intelligence
Scientific Domains:
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Radioastronomy
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Observational Astrophysics
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Time Domain Astronomy
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High-Energy Astrophysics
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Astroparticle Physics
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Galactic and Extragalactic Science
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Cosmology and numerical simulations
