Zobrazeno 1 - 10
of 367
pro vyhledávání: '"Burnaev, E."'
Autor:
Kanin, E. A., Garipova, A. A., Boronin, S. A., Vanovsky, V. V., Vainshtein, A. L., Afanasyev, A. A., Osiptsov, A. A., Burnaev, E. V.
We propose a new method for construction of the absolute permeability map consistent with the interpreted results of well logging and well test measurements in oil reservoirs. Nadaraya-Watson kernel regression is used to approximate two-dimensional s
Externí odkaz:
http://arxiv.org/abs/2301.02585
Autor:
Alsahanova, N., Yarkin, V., Spodarev, E., Bronov, O., Bychenko, V., Marinets, A., Syrkashev, E., Karpov, O., Burnaev, E., Bernstein, A., Alferova, V., Sharaev, M.
Publikováno v:
In Information Sciences January 2025 686
Autor:
Illarionova, S., Hamoudi, R., Zapevalina, M., Fedin, I., Alsahanova, N., Bernstein, A., Burnaev, E., Alferova, V., Khrameeva, E., Shadrin, D., Talaat, I., Bouridane, A., Sharaev, M.
Publikováno v:
In Information Sciences January 2025 686
Reinforcement learning (RL) enjoyed significant progress over the last years. One of the most important steps forward was the wide application of neural networks. However, architectures of these neural networks are typically constructed manually. In
Externí odkaz:
http://arxiv.org/abs/2011.14632
An adversarial attack paradigm explores various scenarios for the vulnerability of deep learning models: minor changes of the input can force a model failure. Most of the state of the art frameworks focus on adversarial attacks for images and other s
Externí odkaz:
http://arxiv.org/abs/2006.11078
Autor:
Morozov, A. D., Popkov, D. O., Duplyakov, V. M., Mutalova, R. F., Osiptsov, A. A., Vainshtein, A. L., Burnaev, E. V., Shel, E. V., Paderin, G. V.
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 machine learning (ML). In multistage fractured completions, post-fracturin
Externí odkaz:
http://arxiv.org/abs/1910.14499
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. It has been estimated that roughly $10$ percent of the insurance indus
Externí odkaz:
http://arxiv.org/abs/1910.03072
Publikováno v:
Proceedings of the International Conference on Computational Science and Applications (ICCSA-2019), 2019
We construct a classification model that predicts if an earthquake with the magnitude above a threshold will take place at a given location in a time range 30-180 days from a given moment of time. A common approach is to use expert forecasts based on
Externí odkaz:
http://arxiv.org/abs/1905.10805
Publikováno v:
16th International Symposium on Neural Networks, ISNN 2019
The main aim of this work is to develop and implement an automatic anomaly detection algorithm for meteorological time-series. To achieve this goal we develop an approach to constructing an ensemble of anomaly detectors in combination with adaptive t
Externí odkaz:
http://arxiv.org/abs/1905.07892
Autor:
Artemov, A. V., Burnaev, E. V.
Publikováno v:
Theory Probab. Appl., 60(1), 126-134, 2016
We consider the problem of optimal estimation of the value of a vector parameter $\thetavector=(\theta_0,\ldots,\theta_n)^{\top}$ of the drift term in a fractional Brownian motion represented by the finite sum $\sum_{i=0}^{n}\theta_{i}\varphi_{i}(t)$
Externí odkaz:
http://arxiv.org/abs/1707.07329