Rezultati pretraživanja
  1. Maths are love except for the related to Hilbert Space and tensor algebra... Animation made in .

  2. The notion of taking the trace of a matrix generalizes to that of taking contraction of or partial traces of density matrices of entangled systems as used in information theory.

  3. 6. tra 2018.
  4. 29. lip 2018.

    Had a great time talking about at University of Zurich for the ifi summer school on Machine Learning - slides and material from my course are online

  5. 9. srp 2019.

    If there is a lesson learned in bringing to , is that is essential to run the unit tests first on the PyTorch and functions. That gives you a whole idea on how to call tensors, extract slices, manage indices, and special functions 4/n

  6. 18. lip 2018.

    Our paper "Constrained Coupled Matrix-Tensor Factorization and its Application in Pattern and Topic Detection" has been accepted at Co-authored with amazing

  7. Thanks to for his new podcast : "Towards Machine Learning in with TensorFlow". A link have been added in my dedicated wikidot page :

  8. follow-on / exchange: Discussing and examples related to and how those examples relate to the mapping problem sets the SERVIR hubs are trying to tackle. 🧐

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  9. 23. sij 2018.

    I've always admired the crazy scientists who can write scary maths that nobody understands or gives two hoots about. Hence, the scribblings on my board. They've been there for the past two years!

  10. Dr. Yang Shi has worked on in : data compression using tensor sketches, extended BLAS computational primitives for in-place tensor contractions, tensor products for multimodal learning tasks. She will be joining as research scientist.

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  11. workshop on starting now

  12. 22. kol 2019.

    How can we combine tensors and GANs? Follow our polynomial approximation and learn how to convert your generator into a polynomial. With , Yannis and Stefanos

  13. are natural language for scientific computing workshop on tensors

  14. 17. lip 2019.

    Full room for , currently explaining the oddities of the rank of when you come from linear algebra tutorial on tensor methods.

  15. 13. svi 2018.
  16. 9. velj 2019.

    Hard to put up with! Though trying to pull off well. though it should be day 35. Consistency is the key, not giving up!

  17. 21. kol 2018.

    and functions amaze me. Not least how they can be used to rotate permeability and recalculate the principal components! Incredible. Working with .

  18. Odgovor korisniku/ci

    That's why you need

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