41 citations · 86 across the 20 of their papers we have counts for
7 papers · 1 filter
Symbolic regression for defect interactions in 2D materials
Mikhail Lazarev, Andrey Ustyuzhanin
Machine learning models have become firmly established across all scientific fields. Extracting features from data and making inferences based on them with neural network models of…
AI Competitions and Benchmarks: Competition platforms
Andrey Ustyuzhanin, Harald Carlens
The ecosystem of artificial intelligence competitions is a diverse and multifaceted landscape, encompassing a variety of platforms that each host numerous competitions annually, al…
Symbolic expression generation via Variational Auto-Encoder
Sergei Popov, Mikhail Lazarev, Vladislav Belavin +2
There are many problems in physics, biology, and other natural sciences in which symbolic regression can provide valuable insights and discover new laws of nature. A widespread Dee…
Learning velocity model for complex media with deep convolutional neural networks
A. Stankevich, I. Nechepurenko, A. Shevchenko +3
The paper considers the problem of velocity model acquisition for a complex media based on boundary measurements. The acoustic model is used to describe the media. We used an open-…
Segmentation of EM showers for neutrino experiments with deep graph neural networks
Vladislav Belavin, Ekaterina Trofimova, Andrey Ustyuzhanin
We introduce a first-ever algorithm for the reconstruction of multiple showers from the data collected with electromagnetic (EM) sampling calorimeters. Such detectors are widely us…
Online detection of failures generated by storage simulator
Kenenbek Arzymatov, Mikhail Hushchyn, Andrey Sapronov +4
Modern large-scale data-farms consist of hundreds of thousands of storage devices that span distributed infrastructure. Devices used in modern data centers (such as controllers, li…