论文标题
tntorch：张张网络学习与pytorch
tntorch: Tensor Network Learning with PyTorch
论文作者
论文摘要
我们提出了TNTORCH，这是一个张量学习框架，该框架支持统一界面下的多个分解（包括CandeComp/Parafac，Tucker和Tensor Train）。借助我们的图书馆，用户可以通过自动差异，无缝的GPU支持以及Pytorch的API的便利性学习和处理低排名的张量。除分解算法外，tntorch还实施了可区分的张量代数，等级截断，互换性，批处理处理，综合张量算术等。
We present tntorch, a tensor learning framework that supports multiple decompositions (including Candecomp/Parafac, Tucker, and Tensor Train) under a unified interface. With our library, the user can learn and handle low-rank tensors with automatic differentiation, seamless GPU support, and the convenience of PyTorch's API. Besides decomposition algorithms, tntorch implements differentiable tensor algebra, rank truncation, cross-approximation, batch processing, comprehensive tensor arithmetics, and more.
