THEORY

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====== News ======

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====== The 8th International Conference on Deep Learning in Computational Physics ======

**June 19-21, 2024 \\ SINP MSU, Moscow, Russia** {{:dlcp2024:call4paper.png?64|}}

**Official website DLCP2024:** [[https://dlcp2024.sinp.msu.ru]]

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.

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 working languages are English and Russian.

===== Organizers =====

||[[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/|{{: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://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 =====

**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.

**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, monitoring networks

**Section 3.** Machine Learning in Natural Sciences
  * Biology and bioinformatics.
  * Engineering sciences.
  * Modern Machine Learning Methods

**The conference will feature:**

  * invited presentations – 30 minutes,
  * regular presentations – 15 minutes,

===== Important dates =====
  * Registration — until June 10, 2024
  * Deadline for abstract submission — **June 3, 2024**
  * Notification of report acceptance — June 10, 2024
  * Conference dates - June 19-21, 2024
  * Paper submission — August 12, 2024

===== Registration and abstract submission =====

The registration and abstract submission should be done via the website: [[:dlcp2024:registration|Registration and abstract submission]].

===== Registration fee ======

To participate in the conference, you must purchase a ticket through the [[https://timepad.ru|TimePad]] service. Organizational support for the conference is provided by the conference partner [[https://iplaboratories.com/ru/|IP Laboratory Russia]].

The ticket price includes organizational expenses, participation support, coffee breaks, preparation of conference materials, including publication of proceedings. \\ 
Accommodation and social events are not included and must be paid for separately by participants.

On site participation:


  * Participant 	  -  6000 ₽ (Early registration, before June 10 - 5000 ₽)
  * Student  		  -  2000 ₽ (Early registration, before June 10 - 1000 ₽)


Online (remote participation):     
  * Рarticipants with accepted report for each - 4000 ₽
  * Students with accepted report for each (first author in the list) - 1000 ₽
  * Online participants without report including co-authors -  free of charge  

If you plan to participate in person or have received confirmation that your report is included in the conference program, then you need to buy a ticket by clicking on the link of <color /lightgrey>[[https://ipaccelerator.timepad.ru/event/2847316/|DLCP2024 event]]</color> on the Timepad service.

//**Attention!** Payment for participation must be made no later than June 18. Otherwise, you will be excluded from the list of participants.//

Please send confirmation of payment to the conference email [[dlcp2024@sinp.msu.ru]].

<color /lightgrey>[[https://ipaccelerator.timepad.ru/event/2847316/|BUY A TICKET FOR THE DLCP2024]]</color>
===== Proceedings =====

After blind peer review, all accepted papers will be published in the conference proceedings as a special issue of the journal [[http://vmu.phys.msu.ru/recent|Moscow University Physics Bulletin]] in 2024 in both electronic and paper form. The journal is published in English by [[https://www.springer.com/journal/11972|Springer]] and indexed in the databases [[https://www.webofscience.com|WoS]] and [[https://www.scopus.com|Scopus]] and is included in the Russian index [[https://elibrary.ru/projects/rsci/rsci.pdf|RCSI]] too.

**We invite three types of submissions:**

INVITED PAPERS until 30 pages \\ 
REGULAR PAPERS describe research not published or submitted elsewhere (12-15 pages). \\ 
SHORT PAPERS may be position papers, descriptions of research prospects, challenges, projects,
ongoing works, or applications (5-9 pages).

===== Place and transportation =====

The Skobeltsyn Institute of Nuclea Physics  of  MSU (Leninskie gory-1, bld.5, Moscow, Russia, near by metro "Universitet"). The ZOOM link will only be sent to registered participants 2 days before the start of the conference.

===== Accommodation =====

Conference participants have to make hotel reservations on their own and in advance. Sorry, NO VISA support.


===== Program committee =====
  * A. Kryukov (SINP MSU, Moscow) — Co-Chair
  * S. Gulev, corresponding member of the RAS (SAIL, IORAS, Moscow) — Co-Chair

  * E. Boos, corresponding member of the RAS     (SINP MSU, Moscow)
  * S. Dolenko (SINP MSU, Moscow)
  * D. Gorbunov, corresponding member of the RAS (INR RAS, Moscow)
  * V. Ilyin (NRC “Kurchatov Institute”, Moscow)
  * M. Krinitskiy (ML4ESlab, MIPT, Moscow)
  * V. Korenkov (MLIT JINR, Dubna)
  * V. Voevodin, corresponding member of the RAS (RCC MSU, Moscow)

===== Organizing committee =====

  * E.G. Boos (SINP MSU, Moscow) -secretary

  * S. Dolenko (SINP MSU, Moscow)
  * M. Krinitskiy (ML4ESlab, MIPT, Moscow)
  * A. Kryukov (SINP MSU, Moscow)
  * A. Suslov (IORAS, Moscow)

===== Contacts =====
All correspondence should be addressed by e-mail: <dlcp2024@sinp.msu.ru>.


===== Partners =====

||[[https://rscgroup.ru|{{:dlcp2024:rsc-logo.png?140|}}]] | Группа компаний [[https://rscgroup.ru/|РСК]] — ведущий российский и хорошо известный в мире разработчик и интегратор «полного цикла» инновационных энергоэффективных, высокоплотных, масштабируемых решений с жидкостным охлаждением для высокопроизводительных вычислений и систем для машинного/глубокого обучения (High-Performance Computing, Machine Learning/Deep Learning), центров обработки данных (ЦОД), Edge Computing решений и интеллектуальных систем хранения данных «по требованию» (storage-on-demand).||
||[[https://iplaboratories.com/ru/|{{:dlcp2024:ilabs-logo2-bw.png?140|}}]] | [[https://iplaboratories.com/ru/|АйПи Лаборатория]] - консалтинговая компания, работающая в области искусственного интеллекта. Мы выпускаем аналитику, делаем образовательные программы, организуем конференции. Наш самый известный проект - Открытая конференция по искусственному интеллекту [[https://opentalks.ai/en|OpenTalks.AI]]||