Stochastic dynamics of neural networks

• Grant number: 17/15587-8
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: September 01, 2017
• End date: November 30, 2019
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Probability
• Principal Investigator: Jefferson Antonio Galves
• Grantee: Ioannis Papageorgiou
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat, AP.CEPID

Abstract

We aim in studying the stochastic dynamics that describe the complex structures of neural networks. The main objective is to understand how the macroscopic behavior of these systems emerge from the behaviour of a large number of components at a microscopic level given some local interaction rules.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

INGLIS, JAMES; PAPAGEORGIOU, IOANNIS. Log-Sobolev Inequalities for Infinite-Dimensional Gibbs Measures with Non-Quadratic Interactions. Markov Processes and Related Fields, v. 25, n. 5, p. 879-897, 2019. (17/15587-8, 13/07699-0)

HODARA, PIERRE; PAPAGEORGIOU, IOANNIS. Poincare-Type Inequalities for Compact Degenerate Pure Jump Markov Processes. MATHEMATICS, v. 7, n. 6, JUN 2019. (13/07699-0, 17/15587-8, 16/17655-8)

PAPAGEORGIOU, IOANNIS. Modified Log-Sobolev Inequality for a Compact Pure Jump Markov Process with Degenerate Jumps. Journal of Statistical Physics, v. 178, n. 6, FEB 2020. (17/15587-8, 13/07699-0)