Causal Reasoning and Counterfactual Probabilistic Programming Framework Using Approximate Inference

摘要

A computer implemented method of performing inference on a generative model,wherein the generative model in a probabilistic program form, said probabilistic program form defining variables and probabilistic relationships between variables, the method comprising:providing at least one of observations or interventions to the generative model;selecting an inference method, wherein the inference method is selected from one of: observational inference, interventional inference or counterfactual inference;performing the selected inference method using an approximate inference method on the generative model; andoutputting a predicted outcome from the results of the inference;wherein approximate inference is performed by inputting an inference query and the model, observations, interventions and inference query are provided as independent parameters such that they can be iterated over and varied independently of each other.