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Simulation Based Inference (SBI)

Lifetime
All levels
9 lessons
0 quizzes
29 students

Requirements

  • Intro to Statistics
  • Intro to Probability
  • Bayesian Statistics
  • R Programming Language
  • Python

In this mini-course we will look at Simulation Based Inference (SBI), also known as Approximate Bayesian Computation (ABC) and Likelihood Free Inference (LFI): a way to conduct inference (either Frequentist or Bayesian) when we cannot compute the likelihood P(X|θ) analytically, though we can still generate samples. In addition to understanding the problem and the different solutions, we will look at examples using both R and Python. The algorithms that we will look into include Rejection ABC, MCMC ABC, Regression Adjustment, SNPE, SNLE and SNRE.