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Zhong-Ping Ji

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Preprint Sep 2026

Minkowski Attractor Networks: Closed-Form Hyperbolic Flows for Visual Representations

Geometric representation learning predominantly scaffolds representations onto flat Euclidean subspaces or compact product tori ($\mathbb{T}^K$). However, flat manifolds possess vanishing curvature and polynomial volume growth, inherently suffering from metric distortion when embedding multi-scale, tree-like visual hie...

Zhong-Ping Ji · 1 citation
Preprint Sep 2026

Ananke: Contractive Torus Attractor Networks

Ananke is introduced, a representation-learning framework that scaffolds latent representations onto a structured product-torus prior, and its flagship visual backbone realization, Contractive Torus Attractor Networks (CTAN), and both exact trigonometric flows and hardware-friendly symplectic dual-shear variants are an...

Zhong-Ping Ji · 2 citations

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