Sampling from Distributions

Multivariate Gaussian Distributions

Basic Variational Inference

Basic Hamiltonian Monte Carlo

Variational Inference for Multivariate Distributions

Priors on Multivariate Linear Functions

Learning Multivariate Linear Functions

Priors on Stochastic Multivariate Linear Functions

Learning Stochastic Multivariate Linear Functions

Learning from Weak and Strong Evidence

Learning about the Reliability of Information Sources

Learning to Interpret Evidence using Regression

A Simple State Space for Sequential Actions

Sequential Planning as Inference

Modeling Sequential Actions with Multiple Agents

Synthetic Data for Learning to Infer Utility

Sharing Global State Across Episodes

Learning to Predict Utility Across Episodes

A Framework for Evaluating Algorithms that Learn to Infer Utility

Evaluating a Regression Predictor on Simple Markovian Actions

Notes on Learning preferences efficiently using side-information (Owain)

Outline of possible generative models (Owain)

Model 1—Utility directly observed, Bias side-info depends on utility (Owain)

Target and side-information but no context (Owain)