Related lectures (17)
Generative Models: Logistic Regression & Gaussian Distribution
Explores generative models, logistic regression, and Gaussian distribution for approximating posterior probabilities and optimizing model performance.
Statistical Vision Problems
Explores statistical vision problems, evaluating algorithms for hidden signal estimation and the challenges of phase transitions.
Bayesian Estimation
Covers the fundamentals of Bayesian estimation, focusing on the application of Bayes' Theorem in scalar estimation.
Estimation & Bayesian Inference
Covers demousing, estimation, Bayesian inference, likelihood, AWGN, and more.
Inference Problems & Spin Glass Game
Covers inference problems related to the Spin Glass Game and the challenges of making mistakes with preb P.
Bayesian Inference: Estimation & Demystification
Covers the concepts of Demystification, Estimation, and Bayesian Inference in the context of Bayesian statistics.
Bayesian Inference: Optimal Estimation
Explores optimal Bayesian inference, denoising, scalar estimation, and phase transitions.
Bayesian Inference: Precision in Gaussian Model
Explores Bayesian inference for precision in the Gaussian model with known mean, using a Gamma prior and discussing subjective vs objective priors.
Applying the learning bound to kernel regression
Discusses the application of the main theorem to least square regression in a RKHS, focusing on LR of the Rademacher bound and Lipschitz constant.
Maximum Likelihood: Inference and Model Comparison
Explores maximum likelihood inference, model selection, and comparing models using likelihood ratios.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.