Information-Driven Design of Imaging Systems

A NeurIPS 2025 paper introduces a framework that evaluates and optimizes imaging systems based on mutual information, not traditional metrics. The method uses noisy measurements and a noise model to quantify how well measurements distinguish objects. It matches state-of-the-art end-to-end methods while requiring less memory, less compute, and no task-specific decoder design.