Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation.
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Updated
May 17, 2017 - Julia
Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation.
eXpression differentiation in Julia
A Julia package for n-dimensional sparse tensors.
Julia package for xtensor-julia
n-dimensional diagonal arrays for Julia
Provides methods for tensor-valued autoregressive modelling, such as estimation, forecasting and impulse response function (IRF) analysis
Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation.
TensorFields with product topology using Grassmann element parameters
A Classical Simulation of the Quantum Game of Life
Statically sized tensors and related operations for Julia
Julia wrapper for TBLIS with TensorOperations.jl
⟨Grassmann-Clifford-Hodge⟩ multilinear differential geometric algebra
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