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        <description>start

The 10th International Conference in Deep Learning in Computational Physics

July, 6-8, 2026 
SINP MSU, Moscow, Russia

Official website DLCP2026: &lt;https://dlcp.sinp.msu.ru&gt;

We are pleased to invite you to participate to the DLCP2026 – The 10th 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 July, 6-8, 2026.</description>
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        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/accommodation?rev=1712406791&amp;do=diff</link>
        <description>Accommodation

Conference participants have to make hotel reservations on their own and in advance. Sorry, NO VISA support.</description>
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        <title>call_abstract</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/call_abstract?rev=1775314706&amp;do=diff</link>
        <description>Abstract submission on DLCP2025

Registration for the conference is open until June 29, 2025.

Deadline for abstract submission —  June 15, 2025

If you have not registered, you must first register on the REGISTRATION page. Ticket service will open soon.

If you have a question please send the mail to</description>
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        <dc:date>2025-06-30T18:55:59+00:00</dc:date>
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        <title>cert</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/cert?rev=1751309759&amp;do=diff</link>
        <description>Сертификат участника

По запросу, участники конференции могут получить сертификат за подпиью сопредседателя конференции, к.ф.-м.н. А.П.Крюкова по форме</description>
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        <description>Important dates

	*  Registration: June 29, 2026
		*  Early registration: June 15, 2026

	*  Deadline for abstract submission: June 15, 2026
	*  Notification of report acceptance: June 22, 2026
	*  Conference dates: July 6-8, 2026
	*  Paper submission: Aug. 3, 2026</description>
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        <dc:date>2026-04-22T14:58:11+00:00</dc:date>
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        <title>fee</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/fee?rev=1776869891&amp;do=diff</link>
        <description>Event ticket



 Before buying a ticket, don&#039;t forget to register for the conference in the REGISTRATION section!

To participate in the conference, you must purchase a ticket through the TimePad service. Organizational support for the conference is provided by the conference partner</description>
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        <dc:date>2026-04-22T15:00:36+00:00</dc:date>
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        <title>news</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/news?rev=1776870036&amp;do=diff</link>
        <description>Registration

22.06.2026

The TICKET service to the conference is available.

06.03.2026

Registration for conference participants is open.

01.02.2026г.

Early registration (reduced price): until June 15, 2026.

DLCP2026 Conference Announcement

01.02.2026г.

ATTENTION! The DLCP2026 conference will be held at Lomonosov Moscow State University. The conference will be held from July 6 to July 8, 2026.</description>
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        <dc:date>2025-07-01T13:59:07+00:00</dc:date>
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        <title>participants</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/participants?rev=1751378347&amp;do=diff</link>
        <description>List of Paticipants

06.06.2025

This list includes all those who have registered on the conference website. The ZOOM link will be sent only to registered participants the day before the conference starts.

If someone did not find themselves on the list, please let us know by email</description>
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        <dc:date>2025-06-24T18:50:04+00:00</dc:date>
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        <title>place</title>
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        <description>Place and transportation

Access to the conference using lists at the security point. 

To enter the building you must have your passport with you. 

SINP MSU
  The Skobeltsyn Institute of Nuclea Physics  of  MSU (Leninskie gory-1, bld.5, Moscow, Russia, near by metro “Universitet”). Room 2-15, second flow.</description>
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        <dc:date>2025-11-09T09:37:50+00:00</dc:date>
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        <title>proceedings</title>
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        <description>Proceedings

Справки

09.11.2025

Справки из редакции о принятии статьи к публикации в специальном выпуске журнала «Moscow University Physics Bulletin» в 2025г.
 [Alimov P.G] 
[Chizhov K.A.] 
[Saraev R.E.] 
[Shorokhov S.G.]</description>
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        <title>program</title>
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        <description>Program

17.06.2025

The list of accepted reports.

The first author is the presenter.

If someone did not find themselves in the list, please inform us by email &lt;dlcp@sinp.msu.ru&gt;

Section 1. Machine Learning in Fundamental Physics

1. Реко...

М.Ю. Зотов</description>
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        <dc:date>2026-04-09T07:41:47+00:00</dc:date>
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        <title>registration</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/registration?rev=1775720507&amp;do=diff</link>
        <description>Регистрация</description>
    </item>
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        <dc:date>2026-04-06T08:39:50+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>registration2</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/registration2?rev=1775464790&amp;do=diff</link>
        <description>Registration on DLCP2025

Registration for the conference is open until June 23, 2025.

If you are going to present a paper, you must submit the paper abstract after registration by filling out the form on the Paper Application page.

Information about accepted papers will be sent to authors on June 23.</description>
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        <dc:format>text/html</dc:format>
        <dc:date>2025-05-01T17:49:02+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>reprints</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/reprints?rev=1746121742&amp;do=diff</link>
        <description>Special Issue: Deep Learning in Computational Physics

Moscow University Physics Bulletin. Vol. XX, Suppl. X, 2025</description>
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        <dc:format>text/html</dc:format>
        <dc:date>2026-01-14T11:24:59+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>review</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/review?rev=1768389899&amp;do=diff</link>
        <description>Статус трудов

14.01.2026

Гранки статей для окончательной правки будут рассылаться авторам после 16 февраля. В них будут выходные данные, включая DOI.</description>
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        <dc:date>2025-08-31T07:31:26+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>schedule</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/schedule?rev=1756625486&amp;do=diff</link>
        <description>Schudule

30/06/2025

[PDF]

* - remote reports

Section 1. Machine Learning in Fundamental Physics

July 2, 2025. SINP MSU, bld.19, room 2-15
 Time  Title  Reporter 11:00-11:45   Welcome coffee &amp; Rigistration   11:45-12:00  Открытие конференции</description>
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        <dc:date>2026-04-22T14:59:01+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
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        <description>start 




About ([Call for Paper]) 

News, 22 Apr.  

Topics

Important Days 

Registration 

Call for Abstract 

Event ticket   

Place &amp; Accommodation 


Contacts

&lt;dlcp@sinp.msu.ru&gt; 


Previous DLCP

DLCP2025 

DLCP2024

Older conferences

DLCP2023 

DLCP2022 / At JINR 

DLCP-2021 on ZOOM 

DLC-2020 on ZOOM 

DLC-2019 at Irkutsk 

DLC-2018 at KIT 

DLC-2018. Kick off

---

Restricted area</description>
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        <dc:date>2025-06-06T14:46:42+00:00</dc:date>
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        <title>social</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/social?rev=1749221202&amp;do=diff</link>
        <description>Social events

Will be announced later.</description>
    </item>
    <item rdf:about="https://theory2.sinp.msu.ru/doku.php/dlcp2026/start?rev=1775463379&amp;do=diff">
        <dc:format>text/html</dc:format>
        <dc:date>2026-04-06T08:16:19+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>start</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/start?rev=1775463379&amp;do=diff</link>
        <description>Last News

Все новости по ссылке News

Registration

22.06.2026

The TICKET service to the conference is available.

06.03.2026

Registration for conference participants is open.

01.02.2026г.

Early registration (reduced price): until June 15, 2026.

→ Read more...

----------</description>
    </item>
    <item rdf:about="https://theory2.sinp.msu.ru/doku.php/dlcp2026/test?rev=1717313851&amp;do=diff">
        <dc:format>text/html</dc:format>
        <dc:date>2024-06-02T07:37:31+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>test</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/test?rev=1717313851&amp;do=diff</link>
        <description>Registration and abstract submission

Регистрация на конференцию открыта до 10 июня 2024г. 

Срок подачи заявок на доклад до 3 июня 2024г 6 июня 2024г .</description>
    </item>
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        <dc:format>text/html</dc:format>
        <dc:date>2025-06-18T15:24:27+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>timetable</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/timetable?rev=1750260267&amp;do=diff</link>
        <description>Timetable (draft)

19.06.2025

[PDF] файл.

Moscow time (MSK), on site and ZOOM 

# - on-line report (17)

Attention! Before the presentation, the speaker must send a presentation in PDF format for posting on the website.

Section 1. Machine Learning in Fundamental Physics</description>
    </item>
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        <dc:format>text/html</dc:format>
        <dc:date>2026-04-05T06:56:32+00:00</dc:date>
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        <title>topics</title>
        <link>https://theory2.sinp.msu.ru/doku.php/dlcp2026/topics?rev=1775372192&amp;do=diff</link>
        <description>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.</description>
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