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QuantumKitHub/TensorOperations.jl

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Julia package for tensor contractions and related operations

8 mentions on Hacker News by 4 people: 0 stories, 8 comments · first 2015-03-08 · latest 2024-04-27

Mentions per year 8 mentions · busiest year 2019 (4)
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  1. …by all the Julia packages (where @ marks a macro), which is @tensor A[i,j] = B[i,k] * C[k,j] (using https://github.com/Jutho/TensorOperations.jl , but see also OMEinsum, Finch, and my Tullio, TensorCast.)
    comment by mcabbott · 2024-04-27 · in Einsum for Tensor Manipulation
  2. Ask and ye shall receive (more than ye bargained for): https://github.com/mcabbott/Tullio.jl https://github.com/Jutho/TensorOperations.jl https://github.com/under-Peter/OMEinsum.jl Tullio.jl is the most powerful and interesting to me of…
    comment by eigenspace · 2021-06-20 · in Julia: Faster than Fortran, cleaner than Numpy
  3. …https://github.com/mcabbott/TensorCast.jl https://github.com/JuliaPhysics/Measurements.jl https://github.com/Jutho/TensorOperations.jl There are many many more, these are just the first that came to mind.
    comment by eigenspace · 2020-03-23 · in Julia 1.4
  4. Matrix chain multiplication can be seen a special case of tensor contraction, and the https://github.com/Jutho/TensorOperations.jl package has an implementation which tries to optimize the contraction order (macro @tensoropt).
    comment by photon-torpedo · 2019-11-22 · in The Linear Algebra Mapping Problem
  5. …which should work on any storage order, and could be taught to interface with such types: * https://github.com/Jutho/TensorOperations.jl * https://github.com/under-Peter/OMEinsum.jl * https://github.com/mcabbott/TensorCast.jl
    comment by mcabbott · 2019-08-20 · in Julia v1.2
  6. …cool ideas in this space. In particular, I think baking in AD functionality is a cool approach. [1] https://github.com/Jutho/TensorOperations.jl [2] https://github.com/mcabbott/TensorCast.jl
    comment by eigenspace · 2019-06-05 · in Julia Summer of Einsum
  7. …you want: "M_ij = A_ik * B_kj" reads @einsum M[i,j] := A[i,k] * B[k,j] Or faster with @tensor from https://github.com/Jutho/TensorOperations.jl & the same notation. I'm not aware of any attempt to distinguish co-vectors; you can have g =…
    comment by mcabbott · 2019-01-23 · in Einstein Summation in Numpy
  8. In Julia it is easy: https://github.com/Jutho/TensorOperations.jl In some fields, e.g. condensed matter physics, you need you need to deal with contracting multidimensional tensors all the time, and with out Einstein notation it would be…
    comment by stared · 2015-03-08 · in Einstein Notation applied in programming