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--- dlcp2025:start [05/03/2025 18:08] – created - external edit 127.0.0.1
+++ dlcp2025:start [05/03/2025 23:57] (current) – [Organizers] admin
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 ====== Last News ======
-{{section>dlcp:news&footer&firstseconly}}
+{{section>dlcp2025:news&footer&firstseconly}}
-====== The 8th International Conference on Deep Learning in Computational Physics ======
+====== The 9th International Conference in Deep Learning in Computational Physics ======
-**June 19-21, 2024 \\ SINP MSU, Moscow, Russia**{{ dlcp2023:see_you.png?200|}}
+**June 30 - July 2, 2025 \\ [[https://siriusuniversity.ru/eng/|Sirius University of Science and Technology]], Russia**
-**Official website DLCP2024:** [[https://dlcp2024.sinp.msu.ru]]
+/**{{ dlcp2023:see_you.png?200|}}**/
-We are pleased to invite you to participate to the DLCP2024 – The 8th International Conference on Deep Learning in Computational Physics which  will  be held  at the Skobeltsin Institute of Nuclear Physics of  Lomonosov Moscow State University (MSU) on June 19-21, 2024.
+**Official website DLCP2025:** [[https://dlcp.sinp.msu.ru]]
+We are pleased to invite you to participate to the DLCP2025 – The 9th International Conference on Deep Learning in Computational Physics which  will  be held  at the SSirius University of Science and Technology on June 30 -- July 02, 2025.
 The conference will be held in a mixed format: face-to-face and remote.
-The conference focuses on the use of machine learning in particle astrophysics and high energy physics, physics of atmosphere and other areas of natural sciences. Topics of interest are various applications of artificial neural networks to physical problems, as well as the development of new modern machine learning methods for analyzing various scientific data, including big data.
+The conference focuses on the use of machine learning in astrophysics and high energy physics, physics of atmosphere and other areas of natural sciences. Topics of interest are various applications of artificial neural networks to physical problems, as well as the development of new modern machine learning methods for analyzing various scientific data, including big data.
 The working languages are English and Russian.
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 ||[[http://www.sinp.msu.ru/en|{{dlcp2023:sinp-logo.png}}]] | [[http://www.sinp.msu.ru|M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of Nuclear Physics (SINP MSU, Moscow, Russia)]] ||
 ||[[https://ocean.ru/en/|{{dlcp:dlcp2024:shirshov-logo.png?128|}}]] | [[https://ocean.ru/en/|Shirshov Institute of Oceanology, Russian Academy of Sciences]] (Moscow, Russia) ||
-||[[https://rcc.msu.ru/en|{{dlcp2023:rcc-logo.png?120}}]] | [[https://rcc.msu.ru/en|Research Computing Center of the Lomonosov Moscow State University (RCC MSU, Moscow, Russia)]] ||
+||[[https://siriusuniversity.ru/|{{ :dlcp2025:sirius-logo.png |}}]] | [[https://siriusuniversity.ru/|Sirius University of Science and Technology]]||
-||[[https://lit.jinr.ru/en|{{dlcp2023:lit-logo.png?120}}]] | [[https://lit.jinr.ru/en|Joint Institute for Nuclear Research, Meshcheryakov Laboratory of Information Technologies (MLIT JINR, Dubna, Russia)]] ||
 ===== The main topics =====
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   * regular presentations – 15 minutes,
+/**
 ===== Important dates =====
   * Registration — until June 10, 2024
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 All correspondence should be addressed by e-mail: <dlcp2024@sinp.msu.ru>.
+**/