Lectures related to Rank correlation

Explores dependence concepts, copulas, correlation fallacies, and rank correlations in statistics.

Covers rank correlations, tail dependence, and copula fitting methods.

Copulas: Dependence Structures and Simulation

Covers copulas, dependence structures, simulation techniques, and properties of copula densities.

Covers copulas, Sklar's Theorem, meta distributions, and various dependence measures like rank correlations and coefficients of tail dependence.

Copulas and Tail Dependence

Explores copulas, rank correlations, and tail dependence measures in risk management.

A Localization Tale: Practical Course by BIOP

Covers practical aspects of using Fiji for everyday tasks in biological imaging.

Digital Image Correlation

Covers digital image correlation, similarity criteria, iterative approaches, and practical applications in 2D and 3D correlation.

Quantitative Risk Management: Copulas and Generative Adversarial Networks

Explores copulas, simulation algorithms, fitting data with rank correlations, and GANs for image generation.

Random Velocity Fields

Explores random velocity fields, discussing moments, correlation, and statistical symmetries.

High-order Correlations in Massive Datasets

Delves into high-order correlations in massive datasets and their importance.

Modeling Elasticity and Coefficients

Explores correlation matrices, regression, variance, confidence intervals, and standardized systems in statistical modeling.

Copulas: Modeling Dependence in Financial Engineering

Explores the fundamentals of copulas and their role in modeling dependence in financial engineering.

Shape from Stereo-1

Explores geometric stereo, epipolar geometry, correlation methods, occlusions, and real-time implementation challenges in stereo vision systems.

Learning Strategies and Rewards

Explores hypothesis testing, mastery goals, student motivation, and the effects of rewards.

Image Processing I: Correlation Measures and Matched Filtering

Explores correlation measures, matched filtering, and feature extraction in image processing.

Linear Independence: Covariance and Statistical Dependence

Explores covariance, statistical dependence, education-fertility relationship, hypothesis testing, and comparison statistics for continuous outcomes.

Network Sampling: Consistency, Models, and Dynamics

Explores network sampling consistency, models, and graph dynamics in real-life scenarios.

Quantitative Risk Management: Linear Strategies

Explores linear strategies in risk management, translating signals into positions and exploiting predictability.

Kalman Filter: Minimal Variance Estimator

Explores the Kalman filter as a minimal variance estimator and its application in estimating position and velocity.

Learning Latent Models in Graphical Structures

Explores learning latent models in graphical structures, focusing on scenarios with incomplete samples and introducing the notion of distance among variables.