Showing 5 of total 5 results (show query)
rikenbit
rTensor:Tools for Tensor Analysis and Decomposition
A set of tools for creation, manipulation, and modeling of tensors with arbitrary number of modes. A tensor in the context of data analysis is a multidimensional array. rTensor does this by providing a S4 class 'Tensor' that wraps around the base 'array' class. rTensor provides common tensor operations as methods, including matrix unfolding, summing/averaging across modes, calculating the Frobenius norm, and taking the inner product between two tensors. Familiar array operations are overloaded, such as index subsetting via '[' and element-wise operations. rTensor also implements various tensor decomposition, including CP, GLRAM, MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements transpose, t-product, and t-SVD, as defined in Kilmer et al. (2013). Some auxiliary functions include the Khatri-Rao product, Kronecker product, and the Hadamard product for a list of matrices.
Maintained by Koki Tsuyuzaki. Last updated 2 years ago.
6 stars 7.65 score 278 scripts 30 dependents
eddelbuettel
rfoaas:R Interface to 'FOAAS'
R access to the 'FOAAS' (F... Off As A Service) web service is provided.
Maintained by Dirk Eddelbuettel. Last updated 5 months ago.
28 stars 5.23 score 6 scripts
bioc
DelayedTensor:R package for sparse and out-of-core arithmetic and decomposition of Tensor
DelayedTensor operates Tensor arithmetic directly on DelayedArray object. DelayedTensor provides some generic function related to Tensor arithmetic/decompotision and dispatches it on the DelayedArray class. DelayedTensor also suppors Tensor contraction by einsum function, which is inspired by numpy einsum.
Maintained by Koki Tsuyuzaki. Last updated 5 months ago.
softwareinfrastructuredatarepresentationdimensionreduction
4 stars 4.68 score 3 scripts
cran
multiway:Component Models for Multi-Way Data
Fits multi-way component models via alternating least squares algorithms with optional constraints. Fit models include N-way Canonical Polyadic Decomposition, Individual Differences Scaling, Multiway Covariates Regression, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis.
Maintained by Nathaniel E. Helwig. Last updated 6 years ago.
3 stars 2.73 score 6 dependents
jhu267
tensorregress:Supervised Tensor Decomposition with Side Information
Implement the alternating algorithm for supervised tensor decomposition with interactive side information. Details can be found in the publication Hu, Jiaxin, Chanwoo Lee, and Miaoyan Wang. "Generalized Tensor Decomposition with features on multiple modes." Journal of Computational and Graphical Statistics, Vol. 31, No. 1, 204-218, 2022 <doi:10.1080/10618600.2021.1978471>.
Maintained by Jiaxin Hu. Last updated 2 years ago.
1.52 score 11 scripts 1 dependents