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SPD Learn

  • Installation
  • User Guide
  • Theory
  • API
  • Examples
  • FAQ
  • Contributing
  • GitHub
  • PyPI
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  • Installation
  • User Guide
  • Theory
  • API
  • Examples
  • FAQ
  • Contributing
  • GitHub
  • PyPI
Translate

Section Navigation

  • Background
    • Scope and Data Representations
    • Geometry Essentials
    • SPD Learn Pipeline and Trivialization
  • Geometric Concepts
  • Numerical Stability
  • Notation
  • Glossary
  • References
  • Theory

Theory#

Mathematical foundations and reference material for SPD Learn.

Start here

Background

  • Data representations (EEG/fMRI covariances)
  • Minimal geometry & metric choices
  • SPDNet pipeline overview
~10 min Read
Core math

Geometric Concepts

  • SPD manifold & Riemannian metrics
  • Exp/Log maps, parallel transport
  • Layer operation visualizations
~20 min Read
Practical

Numerical Stability

  • Dtype-aware thresholds & clamping
  • Configuration for stability
  • Troubleshooting NaN & convergence
~8 min Read
Reference

Notation

  • Manifold symbols (𝒮⁺, Sym, T_P)
  • Distance & metric conventions
  • Layer operation symbols
~3 min Read
Reference

Glossary

  • SPD matrices & Riemannian terms
  • Layer & module definitions
  • Model architecture names
Quick lookup Read
Reference

References

  • Interactive literature map
  • Model family legend
  • Full bibliography & BibTeX
95 papers Read

See also

  • User Guide – Getting started with SPD Learn

  • API Reference – Complete API reference

  • Applied Examples – Practical examples

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