Measurement Model

Measurement models are mathematical frameworks used to represent the relationship between observed data and underlying variables, crucial for diverse fields from image reconstruction to machine learning. Current research focuses on improving the accuracy and efficiency of these models, particularly through the application of advanced algorithms like diffusion posterior sampling and deep equilibrium models, as well as exploring novel query mechanisms for human-in-the-loop learning. These advancements are driving progress in areas such as medical imaging, robotics (e.g., radar odometry), and economic modeling, enabling more robust and accurate inferences from complex data.