Aki Vehtari: On Bayesian Workflow Published 2021-03-29 Download video MP4 360p Recommendations 1:09:07 Paul Bürkner: An introduction to Bayesian multilevel modeling with brms 1:19:49 Andrew Gelman: Introduction to Bayesian Data Analysis and Stan with Andrew Gelman 53:17 The Bayesians are Coming to Time Series 1:08:27 Developing Hierarchical Models for Sports Analytics with Chris Fonnesbeck 56:36 All About that Bayes: Probability, Statistics, and the Quest to Quantify Uncertainty 46:46 Keynote: Andrew Gelman - Data Science Workflow 1:03:31 Scalable Bayesian Inference with Hamiltonian Monte Carlo 1:43:15 Andrew Gelman - Bayes, statistics, and reproducibility (Rutgers, Foundations of Probability) 52:50 Tech talk: A practical introduction to Bayesian hierarchical modelling 2:01:58 Bayesian Inference is Just Counting 1:28:54 Benjamin Goodrich: Introduction to Bayesian Computation Using the rstanarm R Package 52:47 Bayesian Modeling with R and Stan (Reupload) 13:58 How many digits to report and how many iterations to run 53:20 Michael Betancourt: Scalable Bayesian Inference with Hamiltonian Monte Carlo 29:30 Introduction to Bayesian data analysis - part 1: What is Bayes? 57:35 The Statistical Crisis in Science and How to Move Forward by Professor Andrew Gelman 26:31 Frequentism and Bayesianism: What's the Big Deal? | SciPy 2014 | Jake VanderPlas 29:29 Corrie Bartelheimer: A Bayesian Workflow with PyMC and ArviZ | PyData Berlin 2019 1:16:13 Bayesian Multilevel Modelling with {brms} 36:15 Eric J. Ma - An Attempt At Demystifying Bayesian Deep Learning Similar videos 1:10:15 On Bayesian Workflow - Aki Vehtari 29:49 Uncertainty in Bayesian leave-one-out cross-validation based model comparison 25:12 Regularized Horseshoe - Aki Vehtari 50:15 Practical pre-asymptotic diagnostic of Monte Carlo estimates 43:11 BDA 2019 Lecture 4.2 direct simulation, curse of dimensionality, rejection and importance sampling 15:35 BDA 2019 Lecture 7.2 exchangeability 1:05:03 #29 Model Assessment, Non-Parametric Models, And Much More, with Aki Vehtari 18:18 BDA course 1.1 Introduction to uncertainty and modelling 20:04 BDA course 2.3 Priors and prior information 51:27 BDA 2019 Lecture 10.1 Decision analysis 1:17:41 Tutorial: Model assessment, selection and inference after model selection - Aki Vehtari 58:54 [Keynote] A Few of My Favorite Diagnostics (Aki Vehtari) 48:14 BDA 2019 Lecture 12.2 Summary of modeling data collection, linear models, Lasso, and Gaussian proces 39:30 Aki Vehtari: Stan and probabilistic programming (MLSP 2020 tutorial) 50:50 BDA 2019 Lecture 9.1 PSIS-LOO and K-fold cross-validation 1:15:38 Bayesian Workflow 20:20 StanCon 2020. Developer Talk 1. Aki Vehtari. posteriordb: a database More results