dlcp:dlcp2024:topics
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| - | ===== The main topics ===== | ||
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| - | **Section 1.** Machine Learning in Fundamental 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. | ||
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| - | **Section 2.** Machine Learning for Environmental Sciences | ||
| - | * Climate analysis, retrospective analysis and projection | ||
| - | * Statistical modeling of the ocean and atmosphere on various temporal and spatial scales | ||
| - | * Environmental monitoring: remote sensing, instrumental monitoring, observations, | ||
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| - | **Section 3.** Machine Learning in Natural Sciences | ||
| - | * Biology and bioinformatics. | ||
| - | * Engineering sciences. | ||
| - | * Modern Machine Learning Methods | ||
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| - | **The conference will feature:** | ||
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| - | * invited presentations – 30 minutes, | ||
| - | * regular presentations – 15 minutes, | ||