Statistical Finite Element Method

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Related lectures (30)

Page 2 of 3

Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.

Statistical Inference

Covers likelihood ratio statistic, confidence intervals, and hypothesis testing concepts.

Introduction to Inference

Covers the basics of probability theory, random variables, joint probability, and inference.

Probability and Statistics

Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.

Maximum Likelihood Estimation: Multivariate Statistics

Explores maximum likelihood estimation and multivariate hypothesis testing, including challenges and strategies for testing multiple hypotheses.

Optimization-Based Uncertainty Quantification

Explores optimization-based uncertainty quantification for ill-posed inverse problems in the physical sciences, focusing on regularization methods and interval constructions.

Steady-state Kalman Predictor: Examples and Comparison

Discusses the steady-state Kalman predictor, provides examples, and compares Luenberger and Kalman filtering.

Statistical Analysis: Data Exploration and Inference

Covers statistical analysis, emphasizing data exploration and inference to quantify uncertainty and draw conclusions.

Probability and Statistics: Independence and Conditional Probability

Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.

Hypothesis Testing and Confidence Intervals: Key Concepts

Provides an overview of hypothesis testing and confidence intervals in statistics, including practical examples and key concepts.