International Conference on Probability Theory and Stochastic Processes

This track focuses on the fundamental principles of probability theory, including axioms, probability spaces, and key theorems. Contributions exploring the implications of these foundations in various mathematical contexts are encouraged.

This session will delve into various types of stochastic processes, including discrete and continuous-time models. Papers discussing their applications in real-world scenarios and theoretical advancements are welcome.

This track emphasizes the study of random variables, their distributions, and transformations. Submissions that highlight innovative applications in statistics and engineering are particularly encouraged.

This session will explore the theory and applications of Markov processes, including Markov chains and hidden Markov models. Research that bridges theoretical developments with practical applications in diverse fields is sought.

This track is dedicated to the study of martingales and their applications in stochastic analysis. Contributions that investigate new results or methodologies in this area are highly encouraged.

This session focuses on limit theorems, including the Central Limit Theorem and Law of Large Numbers. Papers that provide new insights or applications of these theorems in various disciplines are welcome.

This track examines the properties and applications of Brownian motion in both theoretical and applied contexts. Submissions that explore its role in finance, physics, and other areas are encouraged.

This session will address the theoretical underpinnings and practical applications of queueing theory. Papers that present novel models or case studies in telecommunications, manufacturing, or service systems are invited.

This track focuses on random fields and their applications in spatial statistics. Contributions that discuss new methodologies or applications in environmental science, geostatistics, or image analysis are welcome.

This session will explore the theory of stochastic differential equations and their applications in various fields. Papers that provide new theoretical results or innovative applications in finance, biology, or engineering are encouraged.

This track emphasizes statistical methods used in the analysis of probabilistic models. Contributions that bridge statistical theory with practical applications in risk analysis and decision-making are particularly sought.