Fetching the paper…
Reading the bibliography…
Tensor networks are the main building blocks in a wide variety of computational sciences, ranging from many-body theory and quantum computing to probability and machine learning.
Graph minors. ii. algorithmic aspects of tree-width
Neil Robertson and Paul D. Seymour · 1986
Earlier work this paper cites.
An introduction to chordal graphs and clique trees
Jean RS Blair and Barry Peyton · 1993
Earlier work this paper cites.
A tourist guide through treewidth
Hans L Bodlaender · 1994
Earlier work this paper cites.
Bucket elimination: A unifying framework for probabilistic inference
Rina Dechter · 1997
Earlier work this paper cites.
A complete anytime algorithm for treewidth
Vibhav Gogate and Rina Dechter · 2004
Earlier work this paper cites.
Python for scientific computing
Travis E Oliphant · 2007
Earlier work this paper cites.
Exploring network structure, dynamics, and function using networkx
Aric Hagberg, Pieter Swart, and Daniel S Chult · 2008
Earlier work this paper cites.
Simulating quantum computation by contracting tensor networks
Igor L Markov and Yaoyun Shi · 2008
Earlier work this paper cites.
Tensor network states and geometry
Glen Evenbly and Guifré Vidal · 2011
Earlier work this paper cites.
Planar f-deletion: Approximation, kernelization and optimal fpt algorithms
Fedor V Fomin, Daniel Lokshtanov, Neeldhara Misra, and Saket Saurabh · 2012
Earlier work this paper cites.
Faster identification of optimal contraction sequences for tensor networks
Robert NC Pfeifer, Jutho Haegeman, and Frank Verstraete · 2014
Cited alongside, same era.
Simulation of low-depth quantum circuits as complex undirected graphical models
Sergio Boixo, Sergei V. Isakov, Vadim N. Smelyanskiy, and Hartmut Neven · 2017
Cited alongside, same era.
Hand-waving and interpretive dance: an introductory course on tensor networks
Jacob C Bridgeman and Christopher T Chubb · 2017
Cited alongside, same era.
Breaking the 49-qubit barrier in the simulation of quantum circuits
Edwin Pednault, John A Gunnels, Giacomo Nannicini, Lior Horesh, Thomas Magerlein, Edgar Solomonik, and Robert Wisnieff · 2017
Cited alongside, same era.
Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al · 2017
Cited alongside, same era.
2018 ces: Intel advances quantum and neuromorphic computing research, 2018
Intel · 2018
Later among the works it cites.
Quantum supremacy circuit simulation on sunway taihulight
Riling Li, Bujiao Wu, Mingsheng Ying, Xiaoming Sun, and Guangwen Yang · 2018
Later among the works it cites.
Improving language understanding by generative pre-training
Alec Radford · 2018
Later among the works it cites.
Quantum supremacy using a programmable superconducting processor
Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C Bardin, Rami Barends, Rupak Biswas, Sergio Boixo, Fernando GSL Brandao, David A Buell, et al · 2019
Later among the works it cites.
https://github.com/sboixo/GRCS.git , 2019
Random circuits dataset · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Computing tree decompositions with flowcutter: Pace 2017 submission
Ben Strasser · 2017
Cited alongside, same era.
Classical Simulation of Intermediate-Size Quantum Circuits
Jianxin Chen, Fang Zhang, Cupjin Huang, Michael Newman, and Yaoyun Shi · 2018
Cited alongside, same era.
64-qubit quantum circuit simulation
Zhao-Yun Chen, Qi Zhou, Cheng Xue, Xia Yang, Guang-Can Guo, and Guo-Ping Guo · 2018
Cited alongside, same era.
Ibm q experience, 2018
IBM · 2018
Cited alongside, same era.
Simple graphs do not restrict the analysis of computational complexity of tensor network contractions, as any tensor network can be transformed such that its expression graph is simple. To achieve this, one needs to multiply factors on parallel edges and to contract self-loops. These operations do not significantly increase numerical complexity
Cited in the paper.
Roman Schutski, Danil Lykov, and Ivan Oseledets · 2019
Later among the works it cites.
Positive-instance driven dynamic programming for treewidth
Hisao Tamaki · 2019
Later among the works it cites.
“zhores”—petaflops supercomputer for data-driven modeling, machine learning and artificial intelligence installed in skolkovo institute of science and technology
Igor Zacharov, Rinat Arslanov, Maksim Gunin, Daniil Stefonishin, Andrey Bykov, Sergey Pavlov, Oleg Panarin, Anton Maliutin, Sergey Rykovanov, and Maxim Fedorov · 2019
Later among the works it cites.
Hyper-optimized tensor network contraction
Johnnie Gray and Stefanos Kourtis · 2020
Closest in time.