Table of Contents

Review status

Шаблон рецензии в формате DOC
Шаблон письма с просьбой провести рецензирование: Request for review

Легенда.

Plenary Reports

Corresponding Author and Article Title Date of review Status
M.I.Petrovskiy. DEEP LEARNING METHODS FOR THE TASKS OF CREATING “DIGITAL TWINS” FOR TECHNOLOGICA PROCESSES 07.09.2023 V.Ilyin
Review
Acccept

Track 1. Machine Learning in Fundamental Physics

Corresponding Author and Article Title Date of review Status
Ju.Dubenskaya et al., Generating Synthetic Images of Gamma-Ray Events for Imaging Atmospheric Cherenkov Telescopes Using Conditional Generative Adversarial Networks 30/09/2023 Dudko
Review
Accept
R.R.Fitagdinov. Generation of the ground detector readings of the Telescope Array experiment and the search for anomalies using neural networks 24/09/2023 Demichev
Review
Accept
K.A.Galaktionov / Neural network approach to impact parameter estimation in high-energy collisions using the microchannel plate detector data 21/09/2023 Dudko
Review
Accept
E.O.Gres. The selection of gamma events from IACT images with deep learning methods 30/09/2023 Dudko
Review
Accept
A.Kryukov. Preliminary results of convolutional neural network models in HiSCORE experiment 03/10/2023 Dolenko
Review
Answer
Accept
A.Kryukov. The use of conditional variational autoencoders for simulation of EASs images from IACTs 21/09/2023 Krinitskiy
Review
Answer
Accept
V.S.Latypova / Method for separating extensive air showers by primary mass using machine learning for a SPHERE-type Cherenkov telescope 27/08-01/09/2023 Demichev
review
Accept
A.Y.Leonov. Deep Learning for Angle of Arrival Prediction in the Baikal Neutrino Telescope 21/09/2023 Demichev
Review
Accept
A.V. Matseiko. Application of machine learning methods in Baikal-GVD:background noise rejection and selection of neutrinoinduced events A.Kryukov
Review
Accept
A.D.Zaborenko. Novelty Detection Neural Networks for Model-Independent New Physics Search 21/09/2023 Ilyin
Review
Acccept

Track 2. Machine Learning in Natural Sciences

Corresponding Author and Article Title Date of review Status
M.Borisov. Estimating cloud base height from all-sky imagery using artificial neural networks <27/09/2023 Streltsova
Review
Answer
Consideration
S.Dolenko (A.Guskov). Transfer Learning for Neural Network Solution of an Inverse Problem in Optical Spectroscopy 05/09/2023 V.Roudnev. Review
Acccept
I.M.Gadzhiev. Classification Approach to Prediction of Geomagnetic Disturbances <25/09/2023 Zrelov
Review
Accept
V.Golikov. Client-server application for automated estimation of the material composition of bottom sediments in the >0.1 mm fraction from microphotography using modern deep learning methods 21/09/2023 Ilyin
Review
Acccept
A.Kasatkin. Machine learning techniques for anomaly detection in high-frequency time series of wind speed and greenhouse gas concentration measurements Demichev
Review
Accept
I.Khabutdinov. Identifying cetacean mammals in high-resolution optical imagery using anomaly detection approach employing Machine Learning models 21/09/2023 Dolenko
Review
Answer
Accept
M.Krinitsky. Estimating significant wave height from X-band navigation radar using convolutional neural networks Dudko=Sep22
Review
Answer
Accept
M.A.Ledovskikh. Recognition of skin lesions from image 21/09/2023 Krinitsky
Review
Reject
Demichev
Review
Accept
Answer
Consideration
A.V.Orekhov. Unsupervised Machine Learning Methods for Determining Special Points of the Polymerase Chain Reaction Fluorescence Accumulation Curve 13/09/2023 S.Dolenko.
Review
Accept
S.A.Pavlov. Application of Machine Learning Methods to Numerical Simulation of Hypersonic Flow 05/08/2023 A.Demichev. Review
Answer
Accept
V.Y.Rezvov. Improvement of the AI-based estimation of signifi cant wave height based on preliminary training on synthetic X-band radar sea clutter images <25/09/2023 Streltsova
Review
Accept
O.E.Sarmanova. Decoding fluorescence excitation-emission matrices of carbon dots aqueous solutions with convolutional neural networks to create multimodal nanosensor of metal ions 21/09/2023 Krinitsky
Review
Accept
A.Savin. SMAP sea surface salinity improvement in the Arctic region using machine learning approaches 13/09/2023 V.Roudnev.
Review
Answer
Consideration
A.Tyshko. Automatic detection of acoustic signals from white whales and bottle-nosed dolphins <25/09/2023 Zrelov
Review
Accept
A.V. Vorobev. Machine learning for diagnostics of space weather effects in the Arctic region 21/08/2023 E.Antonova
Review
Acccept-

Track 3. Modern Machine Learning Methods

Corresponding Author and Article Title Date of review Status
N.Y.Bykov / Methods for a Partial Differential Equation Discovery: Application to Physical and Engineering Problems 03/09/2023 M.Stepanova. Review
Acccept
S.Dolenko. Decomposition of Spectral Contour into Gaussian Bands using Improved Modification of Gender Genetic Algorithm 26/08-02/09/2023 M.Stepanova. Review
Acccept
I.Isaev. The study of the integration of physical methods in the neural network solution of the inverse problem of exploration geophysics with variable physical properties of the medium 31/08-0/09/2023 V.Roudnev.
Review
Accept
Z.Kurdoshev. The importance of the number of overfits in time series forecasting by some optimizers and loss functions in neural networks <25/09/2023 Dolenko
Review
Reject
Demichev
Review2
Reject
Fin: Reject
D.N.Polyakov / Hyper-parameter tuning of neural network for high-dimensional problems in the case of Helmholtz equation 21/09/2023 Krinitsky
Review
Accept

Withdrawn papers

Corresponding Author and Article Title Date of review Status
A.Boukhanovsky. Generative AI for large models and digital twins
A.Kryukov. Machine Learning in Gamma Astronomy
L.Dudko. Methodology for the use of neural networks in the data analysis of the collider experiments
A.Hvatov. Robust equation discovery as a machine learning method 21/08/2023 Withdrawn
V.Kalnitsky. Modification of soft connectives in machine learning models 24/08/2023 Withdrawn
A.Polyakov. A technique for the total ozone columns retrieval using spectral measurements of the IKFS-2 instrument 21/08/2023 Withdrawn
A.Shevchenko. Determination of the charge of molecular fragments by machine learning methods 22/08/2023 Withdrawn
A.Vasiliev. The role of artificial intelligence in the preparation of modern scientific and pedagogical staff. The experience of the course “Neural networks and their application in scientific research” of Moscow State University named after M. V. Lomonosov
M.Zotov.Search for Meteors in the Mini-EUSO Orbital Telescope Data with Neural Networks