Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Home

Lecture

Protein Contact Prediction: Pseudolikelihoods and Potts Models

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (36)

Gaussian Mixture Models: Likelihood and Covariance Matrix Log in to Mediaspace to watch this video

Explores statistical independence, Gaussian Mixture Models, and fitting data with Gaussian functions.

Maximum Likelihood Estimation: Linear Models Log in to Mediaspace to watch this video

Explores maximum likelihood estimation in linear models, covering Gaussian noise, covariance estimation, and support vector machines for classification problems.

Elements of Statistics: Probability, Distributions, and Estimation Log in to Mediaspace to watch this video

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

Maximum Likelihood Theory & Applications Log in to Mediaspace to watch this video

Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.

Spin Glasses and Bayesian Estimation Log in to Mediaspace to watch this video

Covers the concepts of spin glasses and Bayesian estimation, focusing on observing and inferring information from a system closely.

Central Limit Theorem: Properties and Applications Log in to Mediaspace to watch this video

Explores the Central Limit Theorem, covariance, correlation, joint random variables, quantiles, and the law of large numbers.

Linear Independence: Covariance and Statistical Dependence Log in to Mediaspace to watch this video

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

Statistical Theory: Inference and Optimality Log in to Mediaspace to watch this video

Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.

Elements of Statistics: Estimation & Distributions Log in to Mediaspace to watch this video

Covers fundamental statistics concepts, including estimation theory, distributions, and the law of large numbers, with practical examples.

Likelihood Inference Log in to Mediaspace to watch this video

Covers iterative weighted least squares, Poisson regression, mixed models, and likelihood ratio statistic.

Maximum Likelihood Estimation: Econometrics Log in to Mediaspace to watch this video

Introduces Maximum Likelihood Estimation in econometrics, covering principles, properties, applications, and specification tests.

Regression: Simple and Multiple Linear Log in to Mediaspace to watch this video

Covers simple and multiple linear regression, including least squares estimation and model diagnostics.

Estimation and Confidence Intervals Log in to Mediaspace to watch this video

Explores parameter estimation, standard errors, and confidence intervals using the central limit theorem and practical examples.

Interval Estimation Log in to Mediaspace to watch this video

Covers the construction of confidence intervals for a normal distribution with unknown mean and variance.

Protein Co-evolutionary Analysis Log in to Mediaspace to watch this video

Explores protein co-evolutionary analysis, covering protein functions, folding, correlations, DCA, and structure prediction tools like AlphaFold 2.

Topic Models Log in to Mediaspace to watch this video

Introduces topic models, covering clustering, GMM, LDA, Dirichlet distribution, and variational inference.

Page 2 of 2