Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation
Dans ces dernières années, plusieurs axes de recherches liées aux tenseurs (matrices multidimensionn...
In numerical multilinear algebra important progress has recently been made. It has been recognized t...
This report documents the program and the outcomes of Dagstuhl Seminar 22101 "Tensor Computations: A...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Tensors.jl is a Julia package that provides efficient computations with symmetric and non-symmetric ...
Tensors are higher-dimensional analogs of matrices, and represent a key data abstraction for many ap...
Computing derivatives of tensor expressions, also known as tensor calculus, is a fundamental task in...
Automated methods for computing derivatives of cost functions are essential to many modern applicati...
Dans ces dernières années, plusieurs axes de recherches liées aux tenseurs (matrices multidimensionn...
In numerical multilinear algebra important progress has recently been made. It has been recognized t...
This report documents the program and the outcomes of Dagstuhl Seminar 22101 "Tensor Computations: A...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Efficient computations with symmetric and non-symmetric tensors with support for automatic different...
Tensors.jl is a Julia package that provides efficient computations with symmetric and non-symmetric ...
Tensors are higher-dimensional analogs of matrices, and represent a key data abstraction for many ap...
Computing derivatives of tensor expressions, also known as tensor calculus, is a fundamental task in...
Automated methods for computing derivatives of cost functions are essential to many modern applicati...
Dans ces dernières années, plusieurs axes de recherches liées aux tenseurs (matrices multidimensionn...
In numerical multilinear algebra important progress has recently been made. It has been recognized t...
This report documents the program and the outcomes of Dagstuhl Seminar 22101 "Tensor Computations: A...
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