BayesCog Summer 2020 Lecture 12 - Model comparison

(1:33:7)

BayesCog Summer 2020 Lecture 01 - Introduction

(1:34:8)

BayesCog Summer 2020 Lecture 05 - Linking data and parameter

(1:9:9)

BayesCog Summer 2020 Lecture 08 - Intro to Stan (P2) and regression models

(1:34:4)

BayesCog Summer 2020 Lecture 13 - Debugging in Stan

(1:32:27)

BayesCog Summer 2020 Lecture 09 - Intro to cognitive modeling \u0026 Rescorla-Wagner model

(1:46:8)

BayesCog Summer 2020 Lecture 11 - Hierarchical Bayesian modeling + Optimizing Stan code

(1:32:16)

BayesCog Summer 2020 Lecture 07 - Intro to Stan (P1) and implementing Binomial model in Stan

(1:32:11)

BayesCog Summer 2020 Lecture 10 - Implementing Rescorla-Wagner in Stan

(1:30:)

BayesCog Summer 2020 Lecture 06 - Grid approximation of Binomial model \u0026 intro to MCMC

(1:33:46)

BayesCog Summer 2020 Lecture 02 - Intro to R/RStudio (Part 1)

(1:45:30)

BayesCog Summer 2020 Lecture 04 - Probability and Bayes' theorem

(1:47:58)

BayesCog Summer 2020 Lecture 03 - Intro to R/RStudio (Part 2)

(1:24:2)

[BayesCog] SoSe 2021 Lecture 07 - Binomial model in Stan

(1:13:26)