Nicolas Huynh
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126
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2026
Active Timepoint Selection for Learning Measure-Valued Trajectories
The paper proposes a novel active learning framework using Linearized Optimal Transport to strategically select measurement timepoints, thereby minimizing uncertainty when inferring continuous probability paths from sparse, high-dimensional biological data.
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