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This is a final group project for Computational Biology (CS167) implementing Tempo (https://bcb.cs.tufts.edu/tempo/) on a unique Parkinson's dataset. This project was contributed to equally by Kevin Kapner, Carlos Lopez-Rodriguez, and Qing Zhu.
Temporal Lifting (TLift), a model-free temporal cooccurrence based score weighting method proposed in "Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting".
[ECCV 2020] QAConv: Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting, and [CVPR 2022] GS: Graph Sampling Based Deep Metric Learning