Lectures related to Rare Events and Extreme Modeling

Supervised Learning with kNN: Regression Model

Covers a simple mathematical model for supervised learning with k-nearest neighbors in regression.

Covers Extreme Value Theory, focusing on GEV and GPD distributions and the POT Model for threshold exceedances.

Covers the Stochastic Block Model and its application in community detection, exploring its mathematical formulation and challenges.

Extended Josephson Junctions: Modeling and Critical Current

Covers the magnetic thickness, short and long junctions, and critical current.

Probability Models: Fundamentals

Introduces the basics of probability models, covering random variables, distributions, and statistical estimation.

Probabilistic Functions: Free Fields and Random Variables

Covers free fields and probabilistic functions, focusing on random variables and their properties.

Machine Learning Theory: High-Dimensional Perspectives

Explores high-dimensional perspectives in machine learning theory, shedding light on new insights and challenges.

Verification and validation

Covers the verification and validation process in numerical flow simulation, ensuring credibility of simulation outcomes.

Parametric Models

Explores statistical estimation, regression models, and model selection in parametric models.

Elements of Statistics: Probability, Distributions, and Estimation

Covers probability theory, distributions, and estimation in statistics, emphasizing accuracy, precision, and resolution of measurements.

Mathematical Analysis: Factorial Generalization and Absorption

Covers the generalization of factorials, mathematical behavior, and absorption phenomena.

Parameter estimation

Covers the concept of parameter estimation using the least square method.

L-Moment Estimation: Probability-Weighted Moments

Covers L-moment estimation, probability-weighted moments, and maximum likelihood inference basics.

Spin Glasses: Fully Connected

Covers the basics of spin glasses and the mathematical equations used to model them.

Pen-and-paper exercises: Session 4

Focuses on pen-and-paper exercises in computational analysis and problem-solving strategies.

Engineering model for capillary sorption

Presents an engineering model for capillary sorption in cementitious materials, focusing on simple experimental analysis and mathematical formulations.

Oil Convection Study

Studies the convection of oil in a baking dish.

Soil Water Dynamics: General Equations and Mathematical Modelling

Explores water dynamics in unsaturated soils, including Darcy's law extension and mathematical modelling.

Extreme Value Theory: Maximum Distribution

Explores extreme value theory, focusing on maximum distribution and different types of distributions based on shape parameters.

Continuous-Time Stochastic Processes: PAM Signal Error Rate

Covers the application of continuous-time stochastic processes to the calculation of the error rate of a PAM signal.