Your first citation is incorrect. It is "VAN DER WALT" (missing V in yours)
Bryan > On Jan 15, 2016, at 10:36 AM, Li Jiajia <jiaji...@gatech.edu> wrote: > > Hi all, > I’m a PhD student in Georgia Tech. Recently, we’re working on a survey > paper about tensor algorithms: basic tensor operations, tensor decomposition > and some tensor applications. We are making a table to compare the > capabilities of different software and planning to include NumPy. We’d like > to make sure these parameters are correct to make a fair compare. Although we > have looked into the related documents, please help us to confirm these. > Besides, if you think there are more features of your software and a more > preferred citation, please let us know. We’ll consider to update them. We > want to show NumPy supports tensors, and we also include "scikit-tensor” in > our survey, which is based on NumPy. > Please let me know any confusion or any advice! > Thanks a lot! :-) > > Notice: > 1. “YES/NO” to show whether or not the software supports the operation or has > the feature. > 2. “?” means we’re not sure of the feature, and please help us out. > 3. “Tensor order” means the maximum number of tensor dimensions that users > can do with this software. > 4. For computational cores, > 1) "Element-wise Tensor Operation (A * B)” includes element-wise > add/minus/multiply/divide, also Kronecker, outer and Katri-Rao products. If > the software contains one of them, we mark “YES”. > 2) “TTM” means tensor-times-matrix multiplication. We distinguish TTM > from tensor contraction. If the software includes tensor contraction, it can > also support TTM. > 3) For “MTTKRP”, we know most software can realize it through the above > two operations. We mark it “YES”, only if an specified optimization for the > whole operation. > > Software Name > > NumPy > > Computational Cores > > Element-wise Tensor Operation (A * B) > > YES > > Tensor Contraction (A Xmn B) > > NO > > TTM ( A Xn B) > > NO > > Matriced Tensor Times Khatri-Rao Product (MTTKRP) > > NO > > Tensor Decomposition > > CP > > NO > > Tucker > > NO > > Hierarchical Tucker (HT) > > NO > > Tensor Train (TT) > > NO > > Tensor Features > > Tensor Order > > Arbitrary > > Dense Tensors > > YES > > Sparse Tensors > > NO ? > > Parallelized > > NO ? > > Software Information > > Application Domain > > General > > Programming Environment > > Python > > Latest Version > > 1.10.4 > Release Date > > 2016 > > Citation: > 1. AN DER WALT, S., COLBERT, S., AND VAROQUAUX, G. The NumPy array: A > structure for efficient numerical computation. Computing in Science > Engineering 13, 2 (March 2011), 22–30. > 2. OLIPHANT, T. E. Python for scientific computing. Computing in Science > Engineering 9, 3 (May 2007), 10–20. > 3. NumPy (Version1.10.4).Available from http://www.numpy.org, Jan 2016. > > Best regards! > Jiajia Li > > ------------------------------------------ > E-mail: jiaji...@gatech.edu > Tel: +1 (404)9404603 > Computational Science & Engineering > Georgia Institute of Technology > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
