Intensity Function

Intensity functions describe the rate of events or changes in a system, finding applications across diverse fields like medical imaging and temporal point process modeling. Current research focuses on improving the accuracy and efficiency of intensity function estimation, particularly through novel neural network architectures and algorithms that directly model cumulative hazard functions or bypass explicit intensity function definition. These advancements enhance the robustness and generalizability of analyses, leading to improved image processing techniques (e.g., for brain MRI and cardiac MR) and more accurate predictions in event-driven systems.