Continuous-Time Machine Learning: A Unified Mathematical Perspective

This survey paper develops a unified mathematical perspective on continuous-time machine learning, addressing how to model temporal dynamics as continuous processes when observations are sampled at arbitrary time points or span long-range horizons. It characterizes the relationships and design trade-offs among major branches of continuous-time ML that have matured in separate research communities.