On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

Trend · papers per month

count % of corpus

← all fields·2 papers on “hyperbolic space” in Differential Geometry · 1 week

Riemannian Deep Learning:Modules, Networks, and Geometriescs.LG

Unified framework for Riemannian deep learning across manifold-valued representations.

problem Deep learning on manifold-valued representations often relies on Euclidean approximations or costly geometric operations.

method Develops reusable neural modules, manifold-specific network architectures, and geometric designs.

result Generalizes batch normalization and multinomial logistic regression to broader classes of manifolds.

Riemannian geometry manifold-valued data deep learning batch normalization log-Euclidean metrics

2026-07-21abs ↗pdf ↗

Riemannian Deep Learning: Modules, Networks, and Geometriescs.LG

Unified framework for Riemannian deep learning across manifold-valued representations.

problem Deep learning on manifold-valued data lacks reusable modules, specific network architectures, and efficient geometric operations.

method Develops reusable neural modules, manifold-specific network architectures, and geometric designs for broad classes of Lie groups and gyrogroups.

result Generalizes batch normalization and multinomial logistic regression to Riemannian manifolds, including SPD and hyperbolic spaces.

Riemannian geometry manifold-valued data deep learning batch normalization log-Euclidean metrics

2026-07-21abs ↗pdf ↗