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  2. Tensor rank decomposition - Wikipedia

    en.wikipedia.org/wiki/Tensor_rank_decomposition

    Practically, this means that a randomly sampled real tensor (from a continuous probability measure on the space of tensors) of size will be a rank-1 tensor with probability zero, a rank-2 tensor with positive probability, and rank-3 with positive probability. On the other hand, a randomly sampled complex tensor of the same size will be a rank-1 ...

  3. Raising and lowering indices - Wikipedia

    en.wikipedia.org/wiki/Raising_and_lowering_indices

    2.3 General rank. 3 See also. ... Download QR code; Print/export Download as PDF; Printable version; ... An example is the metric tensor ...

  4. File:Non-Programmer's Tutorial for Python 3.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Non-Programmer's...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  5. Tensor - Wikipedia

    en.wikipedia.org/wiki/Tensor

    The tensors are classified according to their type (n, m), where n is the number of contravariant indices, m is the number of covariant indices, and n + m gives the total order of the tensor. For example, a bilinear form is the same thing as a (0, 2)-tensor; an inner product is an example of a (0, 2)-tensor, but not all (0, 2)-tensors are inner ...

  6. Rank (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Rank_(linear_algebra)

    Matrix rank should not be confused with tensor order, which is called tensor rank. Tensor order is the number of indices required to write a tensor , and thus matrices all have tensor order 2. More precisely, matrices are tensors of type (1,1), having one row index and one column index, also called covariant order 1 and contravariant order 1 ...

  7. Tensor (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Tensor_(machine_learning)

    In machine learning, the term tensor informally refers to two different concepts (i) a way of organizing data and (ii) a multilinear (tensor) transformation. Data may be organized in a multidimensional array (M-way array), informally referred to as a "data tensor"; however, in the strict mathematical sense, a tensor is a multilinear mapping over a set of domain vector spaces to a range vector ...

  8. Tensor decomposition - Wikipedia

    en.wikipedia.org/wiki/Tensor_decomposition

    A multi-way graph with K perspectives is a collection of K matrices ,..... with dimensions I × J (where I, J are the number of nodes). This collection of matrices is naturally represented as a tensor X of size I × J × K. In order to avoid overloading the term “dimension”, we call an I × J × K tensor a three “mode” tensor, where “modes” are the numbers of indices used to index ...

  9. Tensor contraction - Wikipedia

    en.wikipedia.org/wiki/Tensor_contraction

    For example, the Ricci tensor is a non-metric contraction of the Riemann curvature tensor, and the scalar curvature is the unique metric contraction of the Ricci tensor. One can also view contraction of a tensor field in the context of modules over an appropriate ring of functions on the manifold [ 5 ] or the context of sheaves of modules over ...

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