Related papers: TensorKrowch: Smooth integration of tensor networks in machine learning

TensorKrowch: Smooth integration of tensor networks in machine learning

URL: http://arxiv.org/abs/2306.08595v3
Date: Fri, 31 May 2024 08:39:03 GMT
Title: TensorKrowch: Smooth integration of tensor networks in machine learning
Authors: José Ramón Pareja Monturiol, David Pérez-García, Alejandro Pozas-Kerstjens,
Abstract summary: We introduceKrowch, an open source Python library built on top of PyTorch. Krowch allows users to construct any tensor network, train it, and integrate it as a layer in more intricate deep learning models.
Score: 46.0920431279359
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Tensor networks are factorizations of high-dimensional tensors into networks of smaller tensors. They have applications in physics and mathematics, and recently have been proposed as promising machine learning architectures. To ease the integration of tensor networks in machine learning pipelines, we introduce TensorKrowch, an open source Python library built on top of PyTorch. Providing a user-friendly interface, TensorKrowch allows users to construct any tensor network, train it, and integrate it as a layer in more intricate deep learning models. In this paper, we describe the main functionality and basic usage of TensorKrowch, and provide technical details on its building blocks and the optimizations performed to achieve efficient operation.

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