Machine learning prototype for SPACE applications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F24%3A10256219" target="_blank" >RIV/61989100:27740/24:10256219 - isvavai.cz</a>
Result on the web
<a href="https://events.it4i.cz/event/240/" target="_blank" >https://events.it4i.cz/event/240/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Machine learning prototype for SPACE applications
Original language description
The objective of this webinar was to present the prototype of a machine learning tool to enable the exploration, analysis, and interpretation of the outputs of large-volume cosmological simulations using Representation Learning techniques. The tool efficiently learns a low-dimensional representation of the structure of simulated galaxies in arbitrary physical components, uncovering their intrinsic structural distribution. It also provides an interactive hierarchical visualization of the entire simulation and its compact representation, and scales to arbitrarily large simulations beyond the Exascale era.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů