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Tensor Networks (TN) offer a powerful framework to efficiently represent very high-dimensional objects.
Some mathematical notes on three-mode factor analysis
Ledyard R Tucker · 1966
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Applications of negative dimensional tensors
Roger Penrose · 1971
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Quantum mechanical computers
Richard P Feynman · 1986
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Quantum computational networks
David Elieser Deutsch · 1989
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A statistical evaluation of recent full reference image quality assessment algorithms
H.R. Sheikh, M.F. Sabir, and A.C. Bovik · 2006
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Matrix product state representations
David Perez-García, Frank Verstraete, Michael M Wolf, and J Ignacio Cirac · 2007
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Nonnegative Matrix and Tensor Factorizations
A. Cichocki, R. Zdunek, A.H. Phan, and S.I. Amari · 2009
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Tensor decompositions, alternating least squares and other tales
Pierre Comon, Xavier Luciani, and André LF De Almeida · 2009
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Tensor decompositions and applications
Tamara G Kolda and Brett W Bader · 2009
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Tensor-train decomposition
Ivan V. Oseledets · 2011
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Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data
H. Lu, K.N. Plataniotis, and A. Venetsanopoulos · 2013
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Tensor regression with applications in neuroimaging data analysis
H. Zhou, L. Li, and H. Zhu · 2013
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Fast multivariate spatio-temporal analysis via low rank tensor learning
Mohammad Taha Bahadori, Qi Rose Yu, and Yan Liu · 2014
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Tree adaptive approximation in the hierarchical tensor format
Jonas Ballani and Lars Grasedyck · 2014
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Putting MRFs on a tensor train
Alexander Novikov, Anton Rodomanov, Anton Osokin, and Dmitry Vetrov · 2014
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A practical introduction to tensor networks: Matrix product states and projected entangled pair states
Román Orús · 2014
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Ncon: A tensor network contractor for matlab
Robert NC Pfeifer, Glen Evenbly, Sukhwinder Singh, and Guifre Vidal · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Tensorizing neural networks
Alexander Novikov, Dmitrii Podoprikhin, Anton Osokin, and Dmitry P. Vetrov · 2015
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Bayesian cp factorization of incomplete tensors with automatic rank determination
Qibin Zhao, Liqing Zhang, and Andrzej Cichocki · 2015
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On the expressive power of deep learning: A tensor analysis
Unsupervised generative modeling using matrix product states
Zhao-Yu Han, Jun Wang, Heng Fan, Lei Wang, and Pan Zhang · 2018
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Scalable gaussian processes with billions of inducing inputs via tensor train decomposition
Pavel Izmailov, Alexander Novikov, and Dmitry Kropotov · 2018
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Expressive power of recurrent neural networks
Valentin Khrulkov, Alexander Novikov, and Ivan Oseledets · 2018
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Oscar Mickelin and Sertac Karaman · 2018
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Learning relevant features of data with multi-scale tensor networks
E. Miles Stoudenmire · 2018
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A regularized tensor decomposition method with adaptive rank adjustment for compressed-sensed-domain background subtraction
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Nadav Cohen, Or Sharir, and Amnon Shashua · 2016
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Ultimate tensorization: compressing convolutional and fc layers alike
Timur Garipov, Dmitry Podoprikhin, Alexander Novikov, and Dmitry Vetrov · 2016
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Low-rank regression with tensor responses
Guillaume Rabusseau and Hachem Kadri · 2016
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Supervised learning with tensor networks
Edwin Stoudenmire and David J. Schwab · 2016
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Qibin Zhao, Guoxu Zhou, Shengli Xie, Liqing Zhang, and Andrzej Cichocki · 2016
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Tensor decomposition for signal processing and machine learning
Nicholas D Sidiropoulos, Lieven De Lathauwer, Xiao Fu, Kejun Huang, Evangelos E Papalexakis, and Christos Faloutsos · 2017
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Efficient low rank tensor ring completion
Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron · 2017
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Senlin Xia, Huaijiang Sun, and Beijia Chen · 2018
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Ke Ye and Lek-Heng Lim · 2018
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Tensor regression meets gaussian processes
Rose Yu, Guangyu Li, and Yan Liu · 2018
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Stable als approximation in the tt-format for rank-adaptive tensor completion
Lars Grasedyck and Sebastian Krämer · 2019
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Einconv: Exploring unexplored tensor decompositions for convolutional neural networks
Kohei Hayashi, Taiki Yamaguchi, Yohei Sugawara, and Shin-ichi Maeda · 2019
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Tensorly: Tensor learning in python
Jean Kossaifi, Yannis Panagakis, Anima Anandkumar, and Maja Pantic · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Evolutionary topology search for tensor network decomposition
Chao Li and Sun Sun · 2020
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Tensor networks for language modeling
Jacob Miller, Guillaume Rabusseau, and John Terilla · 2020
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