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cs.LG2025
DiffSDA: Unsupervised Diffusion Sequential Disentanglement Across Modalities
Hedi Zisling, Ilan Naiman, Nimrod Berman +2
Unsupervised representation learning, particularly sequential disentanglement, aims to separate static and dynamic factors of variation in data without relying on labels. This rema…
cs.LG2025
Distilling Two-Timed Flow Models by Separately Matching Initial and Terminal Velocities
Pramook Khungurn, Pratch Piyawongwisal, Sira Sriswasdi +1
A flow matching model learns a time-dependent vector field that generates a probability path that interpolates between a well-known noise dis…