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Vetrov, Dmitrii Petrovich

Statistics Math-Net.Ru
Total publications: 9
Scientific articles: 9
Presentations: 5

Number of views:
This page:908
Abstract pages:2560
Full texts:1291
References:303
Candidate of physico-mathematical sciences (2006)
E-mail:
Website: https://constructor.university/faculty-member/dmitry-vetrov; https://www.hse.ru/staff/dvetrov

https://www.mathnet.ru/eng/person53085
https://scholar.google.com/citations?user=7HU0UoUAAAAJ&hl=en
https://mathscinet.ams.org/mathscinet/MRAuthorID/774421
https://elibrary.ru/author_items.asp?authorid=126068
ISTINA https://istina.msu.ru/workers/556412
https://orcid.org/0000-0001-6863-9028
https://www.webofscience.com/wos/author/record/H-4870-2015
https://www.scopus.com/authid/detail.url?authorId=8382687000
https://www.researchgate.net/profile/Dmitry-Vetrov

Publications in Math-Net.Ru Citations
2024
1. Daniil Tiapkin, Nikita Morozov, Alexey Naumov, Dmitry Vetrov, “Generative flow networks as entropy-regularized RL”, Proc. Mach. Learn. Res. (PMLR), 238 (2024),  4213–4221  mathnet  isi
2017
2. M. V. Figurnov, K. Struminsky, D. P. Vetrov, “Устойчивый к шуму метод обучения вариационного автокодировщика”, Intelligent systems. Theory and applications, 21:2 (2017),  90–109  mathnet
2010
3. D. P. Vetrov, D. A. Kropotov, A. A. Osokin, “Automatic determination of the numbers of components in the EM algorithm for the restoration of a mixture of normal distributions”, Zh. Vychisl. Mat. Mat. Fiz., 50:4 (2010),  770–783  mathnet  mathscinet; Comput. Math. Math. Phys., 50:4 (2010), 733–746  isi  scopus 5
2009
4. D. P. Vetrov, D. A. Kropotov, N. O. Ptashko, “On the achievement of a compromise between the accuracy and stability of classifiers in the problem of choosing the best sound function for Bayesian learning”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2009, no. 15,  47–52  mathnet  elib
5. D. P. Vetrov, D. A. Kropotov, N. O. Ptashko, “On the achievement of a compromise between the accuracy and stability of classifiers in the problem of choosing the best sound function for Bayesian learning”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2009, no. 14,  45–53  mathnet  elib
6. D. P. Vetrov, D. A. Kropotov, N. O. Ptashko, “An efficient method for feature selection in linear regression based on an extended Akaike's information criterion”, Zh. Vychisl. Mat. Mat. Fiz., 49:11 (2009),  2066–2080  mathnet; Comput. Math. Math. Phys., 49:11 (2009), 1972–1985  isi  scopus 2
2007
7. O. M. Vasil'ev, D. P. Vetrov, D. A. Kropotov, “Knowledge representation and acquisition in expert systems for pattern recognition”, Zh. Vychisl. Mat. Mat. Fiz., 47:8 (2007),  1428–1454  mathnet  mathscinet; Comput. Math. Math. Phys., 47:8 (2007), 1373–1397  scopus 2
2005
8. D. P. Vetrov, D. A. Kropotov, “Convex cluster stabilization of classification algorithms as a means for finding collective solutions with high generalization ability”, Zh. Vychisl. Mat. Mat. Fiz., 45:7 (2005),  1321–1328  mathnet  mathscinet  zmath; Comput. Math. Math. Phys., 45:7 (2005), 1276–1282
2003
9. D. P. Vetrov, “The synthesis of correct pattern recognition algorithms with minimal instability”, Zh. Vychisl. Mat. Mat. Fiz., 43:11 (2003),  1754–1760  mathnet  mathscinet  zmath; Comput. Math. Math. Phys., 43:11 (2003), 1687–1693 1

Presentations in Math-Net.Ru
1. Surprising properties of loss landscape in over-parameterized models
D. P. Vetrov
Mathematical Foundations of Artificial Intelligence
October 30, 2024 17:00   
2. Surprising properties of loss landscape in over-parameterized models
D. P. Vetrov

March 28, 2024 18:30
3. Вид функции потерь в нейронных сетях и перспективы ансамблирования
D. P. Vetrov

June 10, 2020 17:30   
4. Оптимизационная постановка задачи (нейро)байесовского вывода
D. P. Vetrov
Problems in Stochastic Analysis
October 15, 2016 15:00   
5. Математика больших данных: тензоры, нейросети, байесовский вывод
D. P. Vetrov
Colloquium of the Faculty of Computer Science
January 22, 2015 16:40   

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