International Conference on Probability in Pure Mathematics

ICPBPM

18th Dec – 19th Dec 2026 Budapest, Hungary

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Registration Summary

Conference ICPBPM

Date 18th Dec – 19th Dec 2026

Location Budapest, Hungary

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Foundations of Probability Theory +

This track explores the fundamental principles and axioms of probability theory, emphasizing rigorous mathematical formulations. Topics include measure-theoretic foundations, probability spaces, and the interplay between probability and pure mathematics.

SDG 4 SDG 9

02 Random Variables and Their Distributions +

This session focuses on the characterization and properties of random variables, including discrete and continuous distributions. Participants will discuss applications of various probability distributions in pure mathematical contexts.

SDG 4 SDG 9

03 Stochastic Processes in Pure Mathematics +

This track examines the role of stochastic processes in pure mathematics, highlighting their theoretical underpinnings and applications. Key topics include Markov processes, martingales, and their convergence properties.

SDG 4 SDG 9

04 Measure Theory and Probability +

This session delves into the integration of measure theory with probability, providing a rigorous framework for understanding random phenomena. Discussions will include Lebesgue integration, sigma-algebras, and measurable functions.

SDG 4 SDG 9

05 Limit Theorems and Asymptotic Analysis +

This track investigates various limit theorems, including the Central Limit Theorem and Law of Large Numbers, within the context of pure mathematics. Asymptotic analysis techniques will also be explored to understand convergence behaviors.

SDG 4 SDG 9

06 Random Fields and Their Applications +

This session focuses on the mathematical theory of random fields, exploring their properties and applications in various domains. Participants will discuss Gaussian fields, stochastic processes on manifolds, and related topics.

SDG 4 SDG 9

07 Martingales and Their Applications +

This track covers the theory of martingales, including their convergence properties and applications in probability theory. Emphasis will be placed on the use of martingales in various mathematical proofs and models.

SDG 4 SDG 9

08 Probability Models in Pure Mathematics +

This session examines various probability models that are foundational to pure mathematics, including their theoretical implications. Participants will discuss model construction, validation, and the role of randomness in mathematical proofs.

SDG 4 SDG 9

09 Random Matrices and Their Properties +

This track explores the theory of random matrices, focusing on their spectral properties and applications in mathematical statistics. Discussions will include the interplay between random matrices and various fields of pure mathematics.

SDG 4 SDG 9

10 Functional Limit Theorems +

This session investigates functional limit theorems, which extend classical limit theorems to functionals of stochastic processes. Participants will explore their implications in both theoretical probability and applications.

SDG 4 SDG 9

11 Advanced Topics in Theoretical Probability +

This track addresses advanced topics in theoretical probability, including ergodic theory, large deviations, and stochastic calculus. Participants are encouraged to present novel research findings and theoretical advancements.

SDG 4 SDG 9