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  1. Home
  2. /Repositories
  3. /pyRiemann/pyRiemann
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repoGitHubTrust 82 · PrimaryPublished 4h agoLive · 24m ago

pyRiemann/pyRiemann

Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Implements

paperCharacterizing Optimizer-Dependent Training Dynamics Through Hessian Eigenvector Displacement and LocalizationpaperFast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity

Covers

newsHamiltonian Neural Networks from a Differential Geometry Perspective [D]

Related across the graph

paperCharacterizing Optimizer-Dependent Training Dynamics Through Hessian Eigenvector Displacement and LocalizationnewsHamiltonian Neural Networks from a Differential Geometry Perspective [D]paperFast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity
Knowledge path·PCharacterizing Optimizer-Dependent Training Dynamics Through Hessian Eigenvector Displacement and Localization→NHamiltonian Neural Networks from a Differential Geometry Perspective [D]→PFast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity→RpyRiemann/pyRiemann

Topics

brain-computer-interfacecovariance-estimationcovariance-matrixeeghermitian-matricesimage-processingmachine-learningpositive-definite-matricespythonradar-image

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Search similar →Knowledge graph →All repos →Full intelligence feed →
Graph trust82Primary
Graph score768