About Elias Teixeira Krainski Elias Teixeira Krainski Research Scientist, Statistics Bayesian computational statistics geospatial statistics spatio-temporal statistics Elias' research focuses on efficient Bayesian methods for practical implementation, spatio and spatio-temporal statistics, INLA. Events Presented Events Feb 22 - Feb 28, 2026 Graphpcor: Prior for Correlation Matrices Elias Teixeira Krainski, Research Scientist, Statistics Feb 26, 12:00 - 13:00 B9 L2 R2325 correlation Bayesian Estimation expert knowledge integration This talk introduces a scalable, graph-based framework for modeling correlation matrices that integrate expert-informed priors. Jan 21 - Jan 27, 2024 On space-time models: models and applications Elias Teixeira Krainski, Research Scientist, Statistics Jan 25, 12:00 - 13:00 B9 L2 H2 H2 Partial differential equations are a mathematical tool widely used to model phenomena in several different fields. A stochastic partial differential equation (SPDE) introduces random forcing to take the nature of real-world observations.
Graphpcor: Prior for Correlation Matrices Elias Teixeira Krainski, Research Scientist, Statistics Feb 26, 12:00 - 13:00 B9 L2 R2325 correlation Bayesian Estimation expert knowledge integration This talk introduces a scalable, graph-based framework for modeling correlation matrices that integrate expert-informed priors.
On space-time models: models and applications Elias Teixeira Krainski, Research Scientist, Statistics Jan 25, 12:00 - 13:00 B9 L2 H2 H2 Partial differential equations are a mathematical tool widely used to model phenomena in several different fields. A stochastic partial differential equation (SPDE) introduces random forcing to take the nature of real-world observations.
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