Learning a Flow to Self-Supervised Representations
Flow-Based Distribution Matching is introduced, a non-adversarial framework that learns this reference-directed geometry through spherical conditional velocity regression that achieves performance nearly on par with DM and remains competitive with existing SSL methods.
Yu-Ling Jiao, Wen-Sen Ma, Hou-Duo Qi et al.
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