Relevant bibliographies by topics / Kolmogorov

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Kolmogorov'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 June 2025

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Journal articles on the topic "Kolmogorov"

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Semenov, A. L., A. Kh Shen, and N. K. Vereshchagin. "Kolmogorov's Last Discovery? (Kolmogorov and Algorithmic Statistics)." Theory of Probability & Its Applications 68, no. 4 (2024): 582–606. http://dx.doi.org/10.1137/s0040585x97t991647.

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RESCORLA, MICHAEL. "A DUTCH BOOK THEOREM AND CONVERSE DUTCH BOOK THEOREM FOR KOLMOGOROV CONDITIONALIZATION." Review of Symbolic Logic 11, no. 4 (2018): 705–35. http://dx.doi.org/10.1017/s1755020317000296.

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AbstractThis article discusses how to update one’s credences based on evidence that has initial probability 0. I advance a diachronic norm, Kolmogorov Conditionalization, that governs credal reallocation in many such learning scenarios. The norm is based upon Kolmogorov’s theory of conditional probability. I prove a Dutch book theorem and converse Dutch book theorem for Kolmogorov Conditionalization. The two theorems establish Kolmogorov Conditionalization as the unique credal reallocation rule that avoids a sure loss in the relevant learning scenarios.
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Bienvenu, Laurent. "Kolmogorov-Loveland Stochasticity and Kolmogorov Complexity." Theory of Computing Systems 46, no. 3 (2009): 598–617. http://dx.doi.org/10.1007/s00224-009-9232-4.

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Vitányi, Paul M. B. "Remembering Kolmogorov." Metascience 20, no. 3 (2011): 509–11. http://dx.doi.org/10.1007/s11016-011-9540-6.

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Rodin, Andrei V. "A.N. KOLMOGOROV’S CALCULUS OF PROBLEMS AND HOMOTOPY TYPE THEORY." Вестник Пермского университета. Философия. Психология. Социология, no. 3 (2022): 368–79. http://dx.doi.org/10.17072/2078-7898/2022-3-368-379.

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In 1932 A.N. Kolmogorov proposed an original version of mathematical intuitionism where the distinc-tion between problems and theorems plays a central role and which differs in its content from the versions of intuitionism developed by A. Heyting and other followers of L. Brouwer. In view of today’s historians and logicians, it remains a controversial point whether this distinction is to be treated as logical or Kol-mogorov’s «problems» should be regarded as propositions, provided the latter term is interpreted intui-tionistically. The popular BHK semantics of intuitionistic logic, so called a
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Tikhomirov, V. M. "The joy of mathematical discovery: To the 120th anniversary of Academician A.N. Kolmogorov." Вестник Российской академии наук 93, no. 4 (2023): 373–83. http://dx.doi.org/10.31857/s0869587323040126.

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This article is dedicated to the memory of the outstanding mathematician of the 20th century, Andrei Nikolaevich Kolmogorov, whose 120th birthday is celebrated this year. The author describes in detail the formation of Kolmogorov as a scientist, the significance of Moscow State University in the scientific life and pedagogical activity of the famous mathematician. Kolmogorov’s contribution to such branches of mathematics as classical analysis, topology, geometry, approximation theory, functional analysis, and probability theory is analyzed, and the contribution of his scientific school to Russ
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Xu, Yifang, Andrew L. Krause, and Robert A. Van Gorder. "Generalist predator dynamics under kolmogorov versus non-Kolmogorov models." Journal of Theoretical Biology 486 (February 2020): 110060. http://dx.doi.org/10.1016/j.jtbi.2019.110060.

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Stoyanov, Jordan M. "Kolmogorov, stochastics in Bulgaria, and probabilistic problems with unexpected solutions." Mathematics and Education in Mathematics 53 (March 16, 2024): 180–97. http://dx.doi.org/10.55630/mem.2024.53.180-197.

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In this talk, I am going to share with the readers my memories of personal meetings with Andrey Nikolaevich Kolmogorov (1903–1987), the content of our conversations, and the fruitful consequences. The reader is familiar with, or could read, the timely prepared recent comprehensive paper [34], presented by N.M. Yanev at the 52nd Spring Conference of the UBM. Included here are several new details about Andrey Nikolaevich and the great influence of the Moscow Probability School on the development of Stochastics in Bulgaria. I have used MathSciNet and introduced the ‘Kolmogorov number’, a ‘collabor
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Sinai, Ya G. "About A. N. Kolmogorov's work on the entropy of dynamical systems." Ergodic Theory and Dynamical Systems 8, no. 4 (1988): 501–2. http://dx.doi.org/10.1017/s0143385700004648.

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In the fall of 1957 A. N. Kolmogorov started lecturing on the theory of dynamical systems and supervised a seminar on the same theme at the Mechanical–Mathematical Department of Moscow State University. He began his lectures with the theory of systems with a pure point spectrum, which he approached from a probabilistic point of view. This approach, undoubtedly, has many advantages. In the seminar we studied Ito's theory of multiple stochastic integrals and, under the supervision of A. N. Kolmogorov, I. V. Girsanov constructed an example of a Gaussian dynamical system with a simple continuous s
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Dietz, Richard. "On Generalizing Kolmogorov." Notre Dame Journal of Formal Logic 51, no. 3 (2010): 323–35. http://dx.doi.org/10.1215/00294527-2010-019.

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Dissertations / Theses on the topic "Kolmogorov"

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Ludvigsson, Gustav. "Kolmogorov Equations." Thesis, Uppsala universitet, Analys och tillämpad matematik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-202845.

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Barletta, Andrea. "Sull'equazione di Kolmogorov." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2010. http://amslaurea.unibo.it/1372/.

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Hearn, John. "Kolmogorov Complexity of Graphs." Scholarship @ Claremont, 2006. https://scholarship.claremont.edu/hmc_theses/182.

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Kolmogorov complexity is a theory based on the premise that the complexity of a binary string can be measured by its compressibility; that is, a string’s complexity is the length of the shortest program that produces that string. We explore applications of this measure to graph theory.
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Pignotti, Michele. "Taylor formula for Kolmogorov equations." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7461/.

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After briefly discuss the natural homogeneous Lie group structure induced by Kolmogorov equations in chapter one, we define an intrinsic version of Taylor polynomials and Holder spaces in chapter two. We also compare our definition with others yet known in literature. In chapter three we prove an analogue of Taylor formula, that is an estimate of the remainder in terms of the homogeneous metric.
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Désilles, Gaël 1971. "Differential Kolmogorov equations for transiting processes." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/49643.

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Pinto, Alexandre Jorge Teixeira Miranda. "Applications of kolmogorov complexity to cryptography." Doctoral thesis, Porto : [s. n.], 2007. http://hdl.handle.net/10216/64295.

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Liu, Xing. "Kolmogorov superposition theorem and its applications." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/30762.

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Hilbert's 13th problem asked whether every continuous multivariate function can be written as superposition of continuous functions of 2 variables. Kolmogorov and Arnold show that every continuous multivariate function can be represented as superposition of continuous univariate functions and addition in a universal form and thus solved the problem positively. In Kolmogorov's representation, only one univariate function (the outer function) depends on and all the other univariate functions (inner functions) are independent of the multivariate function to be represented. This greatly inspired r
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Pinto, Alexandre Jorge Teixeira Miranda. "Applications of kolmogorov complexity to cryptography." Tese, Porto : [s. n.], 2007. http://catalogo.up.pt/F?func=find-b&local_base=FCB01&find_code=SYS&request=000101279.

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Pignotti, Michele <1990&gt. "Averaged stochastic processes and Kolmogorov operators." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amsdottorato.unibo.it/8569/7/tesi_finale.pdf.

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In this thesis we study a class of multidimensional stochastic processes in which a component is the time integral of another. Our interest stems both from the great variety of applications and the challenging structure of the related Kolmogorov backward operators. In fact, while such processes are widely used in physics and finance, the natural geometric framework to study them is considerably far from the standard Euclidean one and still vague. We wish to clarify it developing a new notion of Hölder spaces of any order and proving a Taylor type formula for functions on them. As applic
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Lee, Troy Jeffrey. "Kolmogorov complexity and formula size lower bounds." [S.l. : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2005. http://dare.uva.nl/document/18461.

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Books on the topic "Kolmogorov"

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Fet, I︠A︡ I., and Dmitriĭ Aleksandrovich Pospelov. Kolmogorov i kibernetika. In-t vychislitelʹnoĭ matematiki i matematicheskoĭ geofiziki SO RAN, 2001.

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Zakharov, Vladimir Evgenʹevich. Kolmogorov spectra of turbulence. Springer-Verlag, 1992.

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Prato, Giuseppe. Kolmogorov Equations for Stochastic PDEs. Birkhäuser Basel, 2004.

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Watanabe, Osamu, ed. Kolmogorov Complexity and Computational Complexity. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77735-6.

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Zakharov, Vladimir E., Victor S. L’vov, and Gregory Falkovich. Kolmogorov Spectra of Turbulence I. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-50052-7.

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Da Prato, Giuseppe. Kolmogorov Equations for Stochastic PDEs. Birkhäuser Basel, 2004. http://dx.doi.org/10.1007/978-3-0348-7909-5.

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Bagdasarov, Sergey K. Chebyshev Splines and Kolmogorov Inequalities. Birkhäuser Basel, 1998. http://dx.doi.org/10.1007/978-3-0348-8808-0.

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1958-, Watanabe Osamu, ed. Kolmogorov complexity and computational complexity. Springer-Verlag, 1992.

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Watanabe, Osamu. Kolmogorov Complexity and Computational Complexity. Springer Berlin Heidelberg, 1992.

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Bagdasarov, Sergey K. Chebyshev Splines and Kolmogorov Inequalities. Birkhäuser Basel, 1998.

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Book chapters on the topic "Kolmogorov"

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Cencini, Massimo, Andrea Puglisi, Davide Vergni, and Angelo Vulpiani. "Kolmogorov." In A Random Walk in Physics. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72531-0_17.

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Witt, Kurt-Ulrich, and Martin Eric Müller. "Kolmogorov-Komplexität." In Algorithmische Informationstheorie. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-61694-9_7.

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Belopolskaya, Ya I., and Yu L. Dalecky. "Kolmogorov Equations." In Mathematics and Its Applications. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-2215-0_5.

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Gooch, Jan W. "Kolmogorov-Smirnov Test." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15267.

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Chorin, Alexandre J. "The Kolmogorov Theory." In Vorticity and Turbulence. Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4419-8728-0_4.

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Boffetta, Guido, and Angelo Vulpiani. "Andrey Nikolaevich Kolmogorov." In Mathematical Lives. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13606-1_17.

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Souto, André. "Kolmogorov Complexity Cores." In Programs, Proofs, Processes. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13962-8_42.

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Abalakin, Victor K. "Kolmogorov, Andrei Nikolaevich." In Biographical Encyclopedia of Astronomers. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4419-9917-7_790.

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Dürr, Detlef, Anne Froemel, and Martin Kolb. "Die Kolmogorov-Axiome." In Einführung in die Wahrscheinlichkeitstheorie als Theorie der Typizität. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-52961-4_6.

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Heijden, Petra, Ian T. Durham, İhsan Fazlıoğlu, et al. "Kolmogorov, Andrei Nikolaevich." In The Biographical Encyclopedia of Astronomers. Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-30400-7_790.

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Conference papers on the topic "Kolmogorov"

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Zeydan, Engin, Cristian J. Vaca-Rubio, Luis Blanco, Roberto Pereira, Marius Caus, and Abdullah Aydeger. "F-KANs: Federated Kolmogorov-Arnold Networks." In 2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC). IEEE, 2025. https://doi.org/10.1109/ccnc54725.2025.10976205.

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Kich, Victor A., Jair A. Bottega, Raul Steinmetz, Ricardo B. Grando, Ayano Yorozu, and Akihisa Ohya. "Kolmogorov-Arnold Networks for Online Reinforcement Learning." In 2024 24th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2024. https://doi.org/10.23919/iccas63016.2024.10773080.

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Ataei, Masoud, Mohammad Javad Khojasteh, and Vikas Dhiman. "DAREK - Distance Aware Error for Kolmogorov Networks." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10888425.

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Rabbi, Rawhatur, Joy Datta, Shuvro Ahmed, and Aniqua Nusrat Zereen. "Wildfire Prediction using Convolutional Kolmogorov-Arnold Network." In 2024 13th International Conference on Electrical and Computer Engineering (ICECE). IEEE, 2024. https://doi.org/10.1109/icece64886.2024.11024794.

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Xu, Meiyong, Dongfang Wu, Yutong Wang, et al. "Image transmission and denoising under non-Kolmogorov turbulence." In 15th International Conference on Information Optics and Photonics (CIOP2024), edited by Yue Yang. SPIE, 2024. https://doi.org/10.1117/12.3046703.

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Mehrabian, Ali, Parsa Mojarad Adi, Moein Heidari, and Ilker Hacihaliloglu. "Implicit Neural Representations with Fourier Kolmogorov-Arnold Networks." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10890471.

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Zhong, Kunhua, Yuwen Chen, Wenqiang Yang, et al. "Interpretable Disease Prediction Based on Kolmogorov - Arnold Networks." In 2024 IEEE International Conference on Medical Artificial Intelligence (MedAI). IEEE, 2024. https://doi.org/10.1109/medai62885.2024.00090.

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Karn, Ayush Kumar, Kamal Kumar Gola, Ananya Kapoor, Mridula Singh, Ayush Kumar, and Dheerendra Pratap Singh. "Kolmogorov-Arnold Networks in Dermatology: Skin Lesion Classification." In 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit). IEEE, 2024. https://doi.org/10.1109/globalaisummit62156.2024.10947938.

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Lau, Ranko, Jing Yao, Chenyu Li, Danfeng Hong, and Jocelyn Chanussot. "Deformable Kolmogorov-Arnold Networks For Hyperspectral Image Classification." In 2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2024. https://doi.org/10.1109/whispers65427.2024.10876426.

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Mosterín, Jesús. "Kolmogorov Complexity." In Proceedings of the Annual Meeting of the International Academy of the Philosophy of Science. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812776617_0005.

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Reports on the topic "Kolmogorov"

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Troisi, Louis R. Clustering Systems with Kolmogorov Complexity and MapReduce. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada547540.

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Allen, J. C., and D. Acero. Multiobjective Optimization on Function Spaces: A Kolmogorov Approach. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada439625.

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Ferdaus, Md Meftahul, Mahdi Abdelguerfi, Elias Ioup, et al. KANICE : Kolmogorov-Arnold networks with interactive convolutional elements. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49791.

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We introduce KANICE, a novel neural architecture that combines Convolutional Neural Networks (CNNs) with Kolmogorov-Arnold Network (KAN) principles. KANICE integrates Interactive Convolutional Blocks (ICBs) and KAN linear layers into a CNN framework. This leverages KANs’ universal approximation capabilities and ICBs’ adaptive feature learning. KANICE captures complex, non-linear data relationships while enabling dynamic, context-dependent feature extraction based on the Kolmogorov-Arnold representation theorem. We evaluated KANICE on four datasets: MNIST, Fashion-MNIST, EMNIST, and SVHN, compa
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Isichenko, M. B., W. Horton, D. E. Kim, E. G. Heo, and D. I. Choi. Stochastic diffusion and Kolmogorov entropy in regular and random Hamiltonians. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/7205669.

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Isichenko, M. B., W. Horton, D. E. Kim, E. G. Heo, and D. I. Choi. Stochastic diffusion and Kolmogorov entropy in regular and random Hamiltonians. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/10156433.

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Lavrenov, Igor, Don Resio, and Vladimir Zakharov. Numerical Simulation of Weak Turbulent Kolmogorov Spectrum in Water Surface Waves. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada423736.

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Meyer, Jack, and Robert Rasche. Kolmogorov-Smirnov Tests For Distribution Function Similarity With Applications To Portfolios of Common Stock. National Bureau of Economic Research, 1989. http://dx.doi.org/10.3386/t0076.

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Yu, D., and S. Chakravorty. A Multi-Resolution Approach to the Fokker-Planck-Kolmogorov Equation with Application to Stochastic Nonlinear Filtering and Optimal Design. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada582272.

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Moss, Linda L., Malcolm S. Taylor, and Henry B. Tingey. A Small Sample Power Study of the Anderson-Darling Statistic and a Comparison with the Kolmogorov and the Cramer-Von Mises Statistics. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada215168.

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Markova, Oksana, Serhiy Semerikov та Maiia Popel. СoCalc as a Learning Tool for Neural Network Simulation in the Special Course “Foundations of Mathematic Informatics”. Sun SITE Central Europe, 2018. http://dx.doi.org/10.31812/0564/2250.

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The role of neural network modeling in the learning сontent of special course “Foundations of Mathematic Informatics” was discussed. The course was developed for the students of technical universities – future IT-specialists and directed to breaking the gap between theoretic computer science and it’s applied applications: software, system and computing engineering. CoCalc was justified as a learning tool of mathematical informatics in general and neural network modeling in particular. The elements of technique of using CoCalc at studying topic “Neural network and pattern recognition” of the sp
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