mlsanityData to 7 Oct 2026

TensorNetwork for Machine Learning

arXiv 1906.06329 ↗First posted 7 Jun 2019cs.LG cond-mat.str-el cs.CVcited by 29

Not on the map. Why?

Abstract (arXiv)

We demonstrate the use of tensor networks for image classification with the TensorNetwork open source library. We explain in detail the encoding of image data into a matrix product state form, and describe how to contract the network in a way that is parallelizable and well-suited to automatic gradients for optimization. Applying the technique to the MNIST and Fashion-MNIST datasets we find out-of-the-box performance of 98% and 88% accuracy, respectively, using the same tensor network architecture. The TensorNetwork library allows us to seamlessly move from CPU to GPU hardware, and we see a factor of more than 10 improvement in computational speed using a GPU.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Jun 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 6; 2023: 5; 2024: 4; 2025: 0; 2026: 1.

29 papers.

Sort:

  1. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  2. 2021An end-to-end trainable hybrid classical-quantum classifiercited by 49
  3. 2022Grokking phase transitions in learning local rules with gradient descentcited by 28
  4. 2023Machine learning with tree tensor networks, CP rank constraints, and tensor dropoutcited by 14
  5. 2023Quantum-Inspired Machine Learning: a Surveycited by 11
  6. 2021Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classificationcited by 9
  7. 2021Quantum-inspired event reconstruction with Tensor Networks: Matrix Product Statescited by 9
  8. 2022Classical versus Quantum: comparing Tensor Network-based Quantum Circuits on LHC datacited by 7
  9. 2023Quantized Fourier and Polynomial Features for more Expressive Tensor Network Modelscited by 6
  10. 2024A Matrix Product State Model for Simultaneous Classification and Generationcited by 5
  11. 2021Entangled q-Convolutional Neural Netscited by 4
  12. 2021Tensor network to learn the wavefunction of datacited by 4
17 more
  1. 2022Interaction Decompositions for Tensor Network Regressioncited by 4
  2. 2024Ultra-low latency quantum-inspired machine learning predictors implemented on FPGAcited by 4
  3. 2021Segmenting two-dimensional structures with strided tensor networkscited by 3
  4. 2021Residual Tensor Train: A Quantum-inspired Approach for Learning Multiple Multilinear Correlationscited by 3
  5. 2022Classical Simulation of Variational Quantum Classifiers using Tensor Ringscited by 3
  6. 2021Non-parametric Semi-Supervised Learning in Many-body Hilbert Space with Rescaled Logarithmic Fidelitycited by 2
  7. 2021Patch-based Medical Image Segmentation using Matrix Product State Tensor Networkscited by 2
  8. 2021Differentiable Programming of Isometric Tensor Networkscited by 2
  9. 2022Deep tensor networks with matrix product operatorscited by 2
  10. 2021Representation Theorem for Matrix Product Statescited by 1
  11. 2023The cross-sectional stock return predictions via quantum neural network and tensor networkcited by 1
  12. 2021Tensor Network for Supervised Learning at Finite Temperaturecited by 0
  13. 2022Stack operation of tensor networkscited by 0
  14. 2023Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimizationcited by 0
  15. 2024A Tensor Network Implementation of Multi Agent Reinforcement Learningcited by 0
  16. 2024No-Free-Lunch Theories for Tensor-Network Machine Learning Modelscited by 0
  17. 2026(MPO)2: Multivariate Polynomial Optimization based on Matrix Product Operatorscited by 0