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20172025
most citedA Predictive Model for Steady-State Multiphase Pipe Flow: Machine Learning on Lab Data

103 citations · 171 across the 14 of their papers we have counts for

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Showing 2019Show all

16 papers · 1 filter

cs.LG201916 cited

Understanding Isomorphism Bias in Graph Data Sets

Sergei Ivanov, Sergei Sviridov, Evgeny Burnaev

In recent years there has been a rapid increase in classification methods on graph structured data. Both in graph kernels and graph neural networks, one of the implicit assumptions…

cs.LG20198 cited

Sequence embeddings help to identify fraudulent cases in healthcare insurance

I. Fursov, A. Zaytsev, R. Khasyanov +2

Fraud causes substantial costs and losses for companies and clients in the finance and insurance industries. Examples are fraudulent credit card transactions or fraudulent claims.…

eess.SY2019

Data-driven model for hydraulic fracturing design optimization: focus on building digital database and production forecast

A. D. Morozov, D. O. Popkov, V. M. Duplyakov +6

Growing amount of hydraulic fracturing (HF) jobs in the recent two decades resulted in a significant amount of measured data available for development of predictive models via mach…

cs.HC2019

Understanding Cyber Athletes Behaviour Through a Smart Chair: CS:GO and Monolith Team Scenario

Anton Smerdov, Anastasia Kiskun, Rostislav Shaniiazov +2

eSports is the rapidly developing multidisciplinary domain. However, research and experimentation in eSports are in the infancy. In this work, we propose a smart chair platform - a…

cs.HC2019

Sensors and Game Synchronization for Data Analysis in eSports

Anton Stepanov, Andrey Lange, Nikita Khromov +3

eSports industry has greatly progressed within the last decade in terms of audience and fund rising, broadcasting, networking and hardware. Since the number and quality of professi…

cs.HC2019

Towards Understanding of eSports Athletes' Potentialities: The Sensing System for Data Collection and Analysis

Alexander Korotin, Nikita Khromov, Anton Stepanov +3

eSports is a developing multidisciplinary research area. At present, there is a lack of relevant data collected from real eSports athletes and lack of platforms which could be used…