Interventions and Counterfactuals in Tractable Probabilistic Models: Limitations of Contemporary Transformations

29 Jan 2020 Ioannis Papantonis Vaishak Belle

In recent years, there has been an increasing interest in studying causality-related properties in machine learning models generally, and in generative models in particular. While that is well motivated, it inherits the fundamental computational hardness of probabilistic inference, making exact reasoning intractable... (read more)

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