Active Timepoint Selection for Learning Measure-Valued Trajectories

ArXi:2605.30625v1 Announce Type: cross Inferring continuous probability paths from sparse snapshots is a fundamental challenge in domains like single-cell biology, where high-fidelity data acquisition is often destructive and constrained by prohibitive sequencing costs. This motivates the need for active learning strategies to strategically select optimal measurement times.