Active Timepoint Selection for Learning Measure-Valued Trajectories
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Active Timepoint Selection for Learning Measure-Valued Trajectories
Announce Type: new Abstract: 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.