Inverse problem model

In Inverse Problem, we wish to recover a signal \(X_{true}\) given measurements \(Y\).

\[\mathcal{A}[X_{true}] + \epsilon = Y\]

The goal of inverse problem is to find \(\mathcal{A^{-1}}\).

Most denoising models are based on deep learning.

We use neural network to approximate \(f_\theta \approx \mathcal{A^{-1}}\)