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Siyuan Jiang

2 accepted papers

2026

DeepFRC: An End-to-End Deep Learning Model for Functional Registration and Classification

ICLR 2026poster

Functional data, representing curves or trajectories, are ubiquitous in fields like biomedicine and motion analysis. A fundamental challenge is phase variability—temporal misalignments that obscure underlying patterns and degrade model performance. Current methods often address registration (alignme…

Cited by 0SourcecodeScholar
2026

NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data

ICML 2026poster

Clustering functional data in the presence of phase variation is challenging, as temporal misalignment can obscure intrinsic shape differences and degrade clustering performance. Most existing approaches treat registration and clustering as separate tasks or rely on restrictive parametric assumption…

Cited by 0SourceScholar