semidefinite#
Initialise and compute means and mean blocks in the positive semidefinite cone.
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engine: Differentiable enginefunctional: Functions and functionalsactivation: Activation functions
cmass: Centre of mass
connectopy: Connectopic manifolds
cov: Covariances and correlations
fourier: Frequency-domain filter
graph: Graphs and networks
interpolate: Interpolation and imputation
kernel: Parameterised kernels
matrix: Matrix operations
residualisesemidefinite: Positive semidefinite cone
sparse: Sparse matrix operations
sphere: Spherical coordinates
sylo: Sylo functionsymmap: Symmetric matrix maps
tsconv: Time series convolution
utils: Miscellaneous
window: Random windowing
init: Initialisation schemesatlas: Atlas initialisation
atlasmixins: Atlas mixinsbase: Base initialisations
deltaplusdirichletfreqfilter: Frequency band init
iirfilter: IIR filter initlaplacemapparam: Mapped parameters and parameter mapsMappedParameterDomainMappedParameterIdentityMappedParameterAffineMappedParameterTanhMappedParameterAmplitudeTanhMappedParameterMappedLogitsNormSphereParameterProbabilitySimplexParameterAmplitudeProbabilitySimplexParameterOrthogonalParameterIsochoricParameterClipRenormaliseForcePositiveDefinitePhaseAmplitudeMixinmpblsemidefinite
sylotoeplitzloss: Loss and regularisationLoss: Base class for scalar-valued lossesParameterisedLoss: Extensible class for custom parameterised lossesMSELoss: Mean squared errorNormedLoss: Normed parameter regularisationidentity: Identity functionzero: Zero functiondifference: Elementwise differenceconstraint_violation: Soft constraintsunilateral_loss: Unilateral penaltieshinge_loss: SVM hinge losssmoothness: Backwards differencesbimodal_symmetric: Minimal distance from 2 modesdet_gram: Gramian determinantlog_det_gram: Gram log-determinant lossentropy: Categorical entropykl_divergence: Kullback-Leibler divergencejs_divergence: Jensen-Shannon divergencebregman_divergence: Bregman divergencesequilibrium: Equilibrium losssecond_moment: Second momentsauto_tol: Significance tolerancebatch_corr: Batch-axis correlationqcfc: QC-FC measures and lossreference_tether: Spatial tether to reference pointsinterhemispheric_tether: Inter-hemispheric tethering losscompactness: Compactnessdispersion: Vector dispersionmultivariate_kurtosis: Time series stationarityconnectopy: Generalised connectopymodularity: Relaxed modularitysum_scalarise: Sum scalarisationmean_scalarise: Mean scalarisationmeansq_scalarise: Squared mean scalarisationmax_scalarise: Maximum-value scalarisationnorm_scalarise: Norm scalarisationvnorm_scalarise: Vector norm scalarisationwmean_scalarise: Weighted mean scalarisationselfwmean_scalarise: Self-weighted mean scalarisationLossApply: Selectively apply loss to parametersLossScheme: Scheme for multiple lossesneuro: Neuroscience data utilities
nn: Neural network modules
semidefinite#Initialise and compute means and mean blocks in the positive semidefinite cone.