Man pages for Riemann
Learning with Data on Riemannian Manifolds

acgAngular Central Gaussian Distribution
citiesData : Populated Cities in the U.S.
densityS3 method for mixture model : evaluate density
ERPData : EEG Covariances for Event-Related Potentials
gorillaData : Gorilla Skull
grassmann.optmacgEstimation of Distribution Algorithm with MACG Distribution
grassmann.runifGenerate Uniform Samples on Grassmann Manifold
grassmann.utestTest of Uniformity on Grassmann Manifold
handsData : Left Hands
labelS3 method for mixture model : predict labels
loglkdS3 method for mixture model : log-likelihood
macgMatrix Angular Central Gaussian Distribution
moSLFinite Mixture of Spherical Laplace Distributions
moSNFinite Mixture of Spherical Normal Distributions
orbitalData : Normal Vectors to the Orbital Planes of the 9 Planets
passifloraData : Passiflora Leaves
predict.m2skregPrediction for Manifold-to-Scalar Kernel Regression
riem.clrqCompetitive Learning Riemannian Quantization
riem.coreset18BBuild Lightweight Coreset
riem.distlpDistance between Two Curves on Manifolds
riem.dtwDynamic Time Warping Distance
riem.fanovaFréchet Analysis of Variance
riem.hclustHierarchical Agglomerative Clustering
riem.interpGeodesic Interpolation
riem.interpsGeodesic Interpolation of Multiple Points
riem.isomapIsometric Feature Mapping
riem.kmeansK-Means Clustering
riem.kmeans18BK-Means Clustering with Lightweight Coreset
riem.kmeansppK-Means++ Clustering
riem.kmedoidsK-Medoids Clustering
riem.knnFind K-Nearest Neighbors
riem.kpcaKernel Principal Component Analysis
riem.m2skregManifold-to-Scalar Kernel Regression
riem.m2skregCVManifold-to-Scalar Kernel Regression with K-Fold Cross...
riem.mdsMultidimensional Scaling
riem.meanFréchet Mean and Variation
riem.medianFréchet Median and Variation
riem.nmshiftNonlinear Mean Shift
riem.pdistCompute Pairwise Distances for Data
riem.pdist2Compute Pairwise Distances for Two Sets of Data
riem.pgaPrincipal Geodesic Analysis
riem.rmmlRiemannian Manifold Metric Learning
riem.sammonSammon Mapping
riem.sc05ZSpectral Clustering by Zelnik-Manor and Perona (2005)
riem.scNJWSpectral Clustering by Ng, Jordan, and Weiss (2002)
riem.scSMSpectral Clustering by Shi and Malik (2000)
riem.scULSpectral Clustering with Unnormalized Laplacian
riem.sebFind the Smallest Enclosing Ball
riem.test2bg14Two-Sample Test modified from Biswas and Ghosh (2014)
riem.test2wassTwo-Sample Test with Wasserstein Metric
riem.tsnet-distributed Stochastic Neighbor Embedding
riem.wassersteinWasserstein Distance between Empirical Measures
rmvnormGenerate Random Samples from Multivariate Normal Distribution
spd.geometrySupported Geometries on SPD Manifold
spd.pdistPairwise Distance on SPD Manifold
spd.wassbaryWasserstein Barycenter of SPD Matrices
sphere.convertConvert between Cartesian Coordinates and Geographic...
sphere.runifGenerate Uniform Samples on Sphere
sphere.utestTest of Uniformity on Sphere
splaplaceSpherical Laplace Distribution
spnormSpherical Normal Distribution
stiefel.optSASimulated Annealing on Stiefel Manifold
stiefel.runifGenerate Uniform Samples on Stiefel Manifold
stiefel.utestTest of Uniformity on Stiefel Manifold
wrap.correlationPrepare Data on Correlation Manifold
wrap.euclideanPrepare Data on Euclidean Space
wrap.grassmannPrepare Data on Grassmann Manifold
wrap.landmarkWrap Landmark Data on Shape Space
wrap.multinomialPrepare Data on Multinomial Manifold
wrap.rotationPrepare Data on Rotation Group
wrap.spdPrepare Data on Symmetric Positive-Definite (SPD) Manifold
wrap.spdkPrepare Data on SPD Manifold of Fixed-Rank
wrap.spherePrepare Data on Sphere
wrap.stiefelPrepare Data on (Compact) Stiefel Manifold
Riemann documentation built on March 18, 2022, 7:55 p.m.