Bob’s bees: the importance of using multiple bees (chains) to judge MCMC convergence Published 2018-05-15 Download video MP4 360p Recommendations 06:01 Using bees to demonstrate the importance of overdispersed Markov chains in MCMC 09:21 The importance of step size for Random Walk Metropolis 04:12 FOALS - Mountain At My Gates [Official Music Video] (GoPro Spherical) 28:48 How to write your first Stan program 08:59 Using a Bayes box to calculate the denominator 12:26 Estimating the posterior predictive distribution by sampling 09:18 5 New AI Tools You Should Try 13:10 Introducing Bayes factors and marginal likelihoods 09:10 An introduction to discrete conditional probability distributions. 02:39 MCMC visualization 06:21 An introduction to continuous conditional probability distributions 26:49 Designing for the Unknown | Simon Landry 30:16 How to Create Tazkira form on Ms Word / ساختن فورم تذکره در برنامه ورد Similar videos 02:18 [2-min intro] Revisiting the Gelman-Rubin Diagnostics 10:14 bobs bees 1:35:33 Probabilistic ML - Lecture 5 - Markov Chain Monte Carlo 08:55 Bayesian statistics syllabus 53:23 ep 5 - Sean Meyn: Markov chains, networks, reinforcement learning, beekeeping and jazz 03:22 Factor Analysis - model representation - part 4 (matrix form) 05:42 Example likelihood model: waiting times between beer orders 07:36 What is meant by independent sampling and how can it be used to understand a distribution? 1:01:35 Langevin MCMC: theory and methods More results