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DLCP-2021. Scientific program (CORR2)

June 28-29, 2021

ZOOM

Moscow time (MSK)

June, 28. Astroparticle and High Energy Physics

10:00-10:15 A.Haungs
Welcome words 		dlcp21haungs.pdf
10:15-11:00 L.Kuzmichev, SINP MSU
TAIGA: status, results and perspectives - shift to 14:45
11:00-11:30 Coffee break
11:30-12:00 P.Koundal, IAP , KIT Karlsruhe
Graph Neural Networks and application for Cosmic-Ray Analysis		dlcp21-koundal.pdf
12:00-12:15 E.Gres, ISU, Irkutsk
A.Kryukov, SINP MSU
The preliminary results on analysis of TAIGA-IACT images using Convolutional Neural Networks		dlcp2021-gres.pdf
12:15-12:30 M.Vasyutina, Faculty of Physics, MSU
Gamma/hadron separation for a ground based IACT (imaging atmospheric Cherenkov telescope) in experiment TAIGA using machine learning methods Random Forest		dlcp21-vasyutina.pdf
12:30-12:45 S.Polyakov, SINP MSU
Performance of convolutional neural networks processing simulated IACT images in the TAIGA experiment		dlcp21-polyakov.pdf
12:45-14:45 Lunch "ZOOM Photo"
14:45-15:30 L.Kuzmichev, SINP MSU
TAIGA: status, results and perspectives		dlcp21-kuzmichev.pdf
15:30-15:45 A.Zaborenko, Faculty of Physics, MSU
Application of deep learning technique to an analysis of hard scattering processes at colliders		dlcp21-zaborenko-v2.pdf
15:45-16:00 A.Vlaskina, Faculty of Physics, MSU
Using convolutional neural network for analysis of HiSCORE events		 dlcp2021-vlaskina-v2.pdf
16:00-16:30 Coffee break
16:30-16:45 V.Tokareva, IAP KIT
Using modern machine learning methods on KASCADE data for science and education		dlcp21-tokareva.pdf
16:45-17:00 P.Bezyazeekov, API ISU
Legacy of Tunka-Rex software and data		dlcp21-bezyazeekov.pdf
17:00-17:15 Ju.Dubenskaya, SINP MSU
Modeling images of proton events for the TAIGA project using a generative adversarial network: features of the network architecture and the learning process		dlcp2021-jdubenskaya.pdf

June, 29. Applications and Methods

10:00-10:30 M.Krinitsky, Shirshov Institute of Oceanology, RAS
Identifying partial differential equations of land surface schemes in INM climate models with neural networks		dlcp21-krinitsky.pdf
10:30-10:45 A.Demichev, SINP MSU
Equivariant Gaussian Processes as Limiting Convolutional Networks with Infinite Number of Channels		dlcp21-demichev.pdf
10:45-11:00 I.Gadzhiev S.Dolenko, SINP MSU
A convolutional hierarchical neural network classifier		dlcp21-gadzhiev.pdf
11:00-11:40 Coffee break
11:40-11:55 A.O.Efitorov, SINP MSU
Use of conditional generative adversarial networks to improve representativity of data in optical spectroscopy		dlcp21-efitorov.pdf
11:55-12:10 I.Isaev, SINP MSU
Neural network solution of inverse problems of geological prospecting with discrete output		dlcp21-isaev.pdf
12:10-12:25A.Naumov R.Rybka, National Research Centre “Kurchatov Institute”
The Russian language corpus and a neural network to analyse Internet tweet reports about Covid-19		dlcp21-rybka.pdf
12:25-12:40A.A. Selivanov, NRC «Kurchatov Institute»
EVALUATION OF MACHINE LEARNING METHODS FOR RELATION EXTRACTION BETWEEN DRUG ADVERSE EFFECTS AND MEDICATIONS IN RUSSIAN TEXTS OF INTERNET USER REVIEWS		dlcp21-selivanov.pdf
12:40-12:55N.V.Abasov, Melentiev Energy Systems Institute SB RAS
The technology of long-term forecasting of water inflow into reservoirs using a multi-parameter neural network		dlcp21-abasov.pdf
12:55-14:45 Lunch"ZOOM Photo"
14:45-16:00Round table: Machine learning in Modern Physics
Moderator: A.Kryukov, SINP MSU
16:00Close workshop
dlcp21/program.txt · Last modified: 24/08/2021 20:22 by kryukov