Multiscale CMH scanning generalizes the classic test to continuous spaces, achieving consistency for conditional independence testing by conditioning on marginal order statistics without requiring large stratum sizes.
Microsoft Research, Redmond , volume=
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V-JEPA models trained only on feature prediction from 2 million public videos achieve 81.9% on Kinetics-400, 72.2% on Something-Something-v2, and 77.9% on ImageNet-1K using frozen ViT-H/16 backbones.
citing papers explorer
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Multiscale Cochran-Mantel-Haenszel Scanning for Conditional Dependency
Multiscale CMH scanning generalizes the classic test to continuous spaces, achieving consistency for conditional independence testing by conditioning on marginal order statistics without requiring large stratum sizes.
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Revisiting Feature Prediction for Learning Visual Representations from Video
V-JEPA models trained only on feature prediction from 2 million public videos achieve 81.9% on Kinetics-400, 72.2% on Something-Something-v2, and 77.9% on ImageNet-1K using frozen ViT-H/16 backbones.