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+====== DLCP-2021. Scientific program (CORR2) ======
+{{ dlcp2021:close.png?200|}}
+**June 28-29, 2021**
+//ZOOM//
+//Moscow time (MSK)//
+/**
+Invited presentation - 45 min \\
+Long presentation - 30 min \\
+Short presentation - 15 min
+**/
+===== June, 28. Astroparticle and High Energy Physics =====
+^^ 10:00-10:15  ^ **A.Haungs** \\ Welcome words ^{{ dlcp2021:dlcp21haungs.pdf |}} ||
+|| 10:15-11:00  | <del>**L.Kuzmichev**, SINP MSU \\ TAIGA: status, results and perspectives</del> - shift to 14:45|||
+^^ 11:00-11:30  ^ Coffee break ^ ||
+|| 11:30-12:00  | **P.Koundal**, IAP , KIT Karlsruhe \\ [[dlcp2021:abstracts#Graph Neural Networks and application for Cosmic-Ray Analysis|Graph Neural Networks and application for Cosmic-Ray Analysis]]|{{ dlcp2021:dlcp21-koundal.pdf }} ||
+|| 12:00-12:15  | **E.Gres**, ISU, Irkutsk \\ A.Kryukov, SINP MSU \\  [[dlcp2021:abstracts#The preliminary results on analysis of TAIGA-IACT images using Convolutional Neural Networks|The preliminary results on analysis of TAIGA-IACT images using Convolutional Neural Networks]]|{{ dlcp2021:dlcp2021-gres.pdf }} ||
+|| 12:15-12:30  | **M.Vasyutina**, Faculty of Physics, MSU \\ [[dlcp2021:abstracts#Gamma/hadron separation for a ground based IACT (imaging atmospheric Cherenkov telescope) in experiment TAIGA using machine learning methods Random Forest|Gamma/hadron separation for a ground based IACT (imaging atmospheric Cherenkov telescope) in experiment TAIGA using machine learning methods Random Forest]]|{{ dlcp2021:dlcp21-vasyutina.pdf }} ||
+|| 12:30-12:45  | **S.Polyakov**, SINP MSU \\ [[dlcp2021:abstracts#Performance of convolutional neural networks processing simulated IACT images in the TAIGA experiment|Performance of convolutional neural networks processing simulated IACT images in the TAIGA experiment]]|{{ dlcp2021:dlcp21-polyakov.pdf }} ||
+^^ 12:45-14:45  ^ Lunch^ [[dlcp2021:pictures|"ZOOM Photo"]] ||
+|| 14:45-15:30  | **L.Kuzmichev**, SINP MSU \\ [[dlcp2021:abstracts#taigastatus results and perspectives|TAIGA: status, results and perspectives]]|{{ dlcp2021:dlcp21-kuzmichev.pdf |}}  ||
+|| 15:30-15:45  | **A.Zaborenko**, Faculty of Physics, MSU \\ [[dlcp2021:abstracts#Application of deep learning technique to an analysis of hard scattering processes at colliders|Application of deep learning technique to an analysis of hard scattering processes at colliders]]|{{ dlcp2021:dlcp21-zaborenko-v2.pdf }} ||
+|| 15:45-16:00  | **A.Vlaskina**, Faculty of Physics, MSU \\ [[dlcp2021:abstracts#Using convolutional neural network for analysis of HiSCORE events|Using convolutional neural network for analysis of HiSCORE events]]| {{ dlcp2021:dlcp2021-vlaskina-v2.pdf }} ||
+^^ 16:00-16:30  ^ Coffee break^ ||
+|| 16:30-16:45  | **V.Tokareva**, IAP KIT \\  [[dlcp2021:abstracts#Using modern machine learning methods on KASCADE data for science and education|Using modern machine learning methods on KASCADE data for science and education]]|{{ dlcp2021:dlcp21-tokareva.pdf }} ||
+|| 16:45-17:00  | **P.Bezyazeekov**, API ISU \\ [[dlcp2021:abstracts#Legacy of Tunka-Rex software and data|Legacy of Tunka-Rex software and data]]|{{ dlcp2021:dlcp21-bezyazeekov.pdf |}} ||
+|| 17:00-17:15  | **Ju.Dubenskaya**, SINP MSU \\ [[dlcp2021:abstracts#Modeling images of proton events for the TAIGA project using a generative adversarial network: features of the network architecture and the learning process|Modeling images of proton events for the TAIGA project using a generative adversarial network: features of the network architecture and the learning process]]|{{ dlcp2021:dlcp2021-jdubenskaya.pdf }} ||
+===== June, 29. Applications and Methods =====
+||10:00-10:30| **M.Krinitsky**, Shirshov Institute of Oceanology, RAS \\ [[dlcp2021:abstracts#Identifying_partial_differential_equations_of_land_surface_schemes_in_INM_climate_models_with_neural_networks|Identifying partial differential equations of land surface schemes in INM climate models with neural networks]]|{{ dlcp2021:dlcp21-krinitsky.pdf |}} ||
+||10:30-10:45| **A.Demichev**, SINP MSU \\ [[dlcp2021:abstracts#Equivariant_Gaussian_Processes_as_Limiting_Convolutional Networks with Infinite Number of Channels|Equivariant Gaussian Processes as Limiting Convolutional Networks with Infinite Number of Channels]]|{{ dlcp2021:dlcp21-demichev.pdf |}}||
+||10:45-11:00| **<del>I.Gadzhiev</del> S.Dolenko**, SINP MSU \\ [[dlcp2021:abstracts#A_convolutional_hierarchical_neural_network_classifier|A convolutional hierarchical neural network classifier]]|{{ dlcp2021:dlcp21-gadzhiev.pdf |}} ||
+^^11:00-11:40^ Coffee break^ ||
+||11:40-11:55| **A.O.Efitorov**, SINP MSU \\ [[dlcp2021:abstracts#Use of conditional generative adversarial networks to improve representativity of data in optical spectroscopy|Use of conditional generative adversarial networks to improve representativity of data in optical spectroscopy]]|{{ dlcp2021:dlcp21-efitorov.pdf |}} ||
+||11:55-12:10| **I.Isaev**, SINP MSU \\ [[dlcp2021:abstracts#Neural network solution of inverse problems of geological prospecting with discrete output|Neural network solution of inverse problems of geological prospecting with discrete output]]|{{ dlcp2021:dlcp21-isaev.pdf |}} ||
+||12:10-12:25|**<del>A.Naumov</del> R.Rybka**, National Research Centre “Kurchatov Institute” \\ [[dlcp2021:abstracts#The Russian language corpus and a neural network to analyse Internet tweet reports about Covid-19|The Russian language corpus and a neural network to analyse Internet tweet reports about Covid-19]]|{{ dlcp2021:dlcp21-rybka.pdf |}} ||
+||12:25-12:40|**A.A. Selivanov**, NRC «Kurchatov Institute» \\ [[dlcp2021:abstracts#EVALUATION OF MACHINE LEARNING METHODS FOR RELATION EXTRACTION BETWEEN DRUG ADVERSE EFFECTS AND MEDICATIONS IN RUSSIAN TEXTS OF INTERNET USER REVIEWS|EVALUATION OF MACHINE LEARNING METHODS FOR RELATION EXTRACTION BETWEEN DRUG ADVERSE EFFECTS AND MEDICATIONS IN RUSSIAN TEXTS OF INTERNET USER REVIEWS]]|{{ dlcp2021:dlcp21-selivanov.pdf |}} ||
+||12:40-12:55|**N.V.Abasov**, Melentiev Energy Systems Institute SB RAS \\ [[dlcp2021:abstracts#The technology of long-term forecasting of water inflow into reservoirs using a multi-parameter neural network|The technology of long-term forecasting of water inflow into reservoirs using a multi-parameter neural network]]|{{ dlcp2021:dlcp21-abasov.pdf |}} ||
+^^12:55-14:45^ Lunch^[[dlcp2021:pictures|"ZOOM Photo"]] ||
+||14:45-16:00|**Round table: Machine learning in Modern Physics** \\ Moderator: A.Kryukov, SINP MSU| ||
+^^16:00^**Close workshop**^ ||