Kernel Quantum Probability Library
The KQP library aims at providing tools for working with quantums probabilities

Data Structures  
class  kqp::Dense< Scalar > 
A feature matrix where vectors are dense vectors in a fixed dimension. More...  
class  kqp::FeatureList< FVector > 
A class that supposes that feature vectors know how to compute their inner product, i.e. inner(a,b) is defined. More...  
class  kqp::KernelSumSpace< Scalar > 
A feature matrix where vectors are sparse vectors in a high dimensional space. More...  
class  kqp::Sparse< Scalar > 
A feature matrix where vectors are sparse vectors in a high dimensional space. More...  
class  kqp::SparseDense< Scalar > 
A feature matrix where vectors are in a dense subspace (in the canonical basis). More...  
class  kqp::FeatureMatrixBase< Scalar > 
Base for all feature matrix classes. More...  
Feature matrices are used to represent a set of feature vector. In a finite vectorial space, this is typically a matrix.