Can we use conditional GANs to show causality in our data?
I tried a Conditional GAN and I want to know how can I convert it into a Causal one.
Can we use conditional GANs to show causality in our data?
I tried a Conditional GAN and I want to know how can I convert it into a Causal one.
Generally speaking, there is no quick fix that can just make any complex ML model into a causal one (this applies to GANs as much as to anything else). It all depends on what data you have and what causal relationships you hope to find or estimate.
For example, if you have data with a lot of interventions (e.g. data collected through many controlled experiments), you may be able to leverage the difference in outcomes between the experiments to estimate causal effects. If you have only an observational dataset, as is the standard for many vanilla machine learning tasks, finding causal relationships is extremely difficult.