Track 1. Machine Learning in Physics

• Machine learning methods in particle astrophysics and high energy physics.
• Fast event generators based on machine learning for simulation of physics phenomena.
• Multi-messenger data analysis of experimental data.
• Application machine learning for data analysis in megascience facilities.

Track 2. Modern Machine Learning Methods

• Convolutional neural networks.
• Recurrent neural networks.
• Graph neural networks.
• Modern trends in machine learning.

Track 3. Machine Learning in Natural Sciences

• Biology and bioinformatics.
• Engineering sciences.
• Climate prediction and Earth monitoring.

Track 4. Machine Learning in Education

• Machine learning in High education.
• Outreach knowledge in machine learning