Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent

Riccardo Barbano, Chen Zhang, Simon Arridge +1

Recent advances in reconstruction methods for inverse problems leverage powerful data-driven models, e.g., deep neural networks. These techniques have demonstrated state-of-the-art…