Forward Sampling
Explore how forward sampling helps estimate probabilities in quantum Bayesian networks by generating instances based on conditional probability tables. Understand the process of creating multiple samples to approximate distributions and how quantum simulators apply this method efficiently to solve classification tasks.
We'll cover the following...
We'll cover the following...
In the previous chapter Bayesian Inference, we learned how to apply a variational method to learn a hidden variable. Variational methods approximate the distribution of a hidden variable analytically.
Sampling-based methods work differently. Instead of calculating the hidden distribution, they approximate it empirically. The principle is straightforward. These methods repeatedly select an instance and ...