Fetching the paper…
Reading the bibliography…
For quantum systems with a total dimension greater than six, the positive partial transposition (PPT) criterion is sufficient but not necessary to decide the non-separability of quantum states.
Ra olshen and cj stone,“
L Breiman and JH Friedman · 1984
Earlier work this paper cites.
A fuzzy k-nearest neighbor algorithm
James M Keller, Michael R Gray, and James A Givens · 1985
Earlier work this paper cites.
Principal component analysis
Svante Wold, Kim Esbensen, and Paul Geladi · 1987
Earlier work this paper cites.
Quantum states with einstein-podolsky-rosen correlations admitting a hidden-variable model
Reinhard F Werner · 1989
Earlier work this paper cites.
Artificial neural networks technology
Dave Anderson and George McNeill · 1992
Earlier work this paper cites.
Algorithms for quantum computation: Discrete logarithms and factoring
Peter W Shor · 1994
Earlier work this paper cites.
Separability criterion for density matrices
Asher Peres · 1996
Earlier work this paper cites.
Separability of mixed states: necessary and sufficient conditions
Michał Horodecki, Paweł Horodecki, and Ryszard Horodecki · 1996
Earlier work this paper cites.
Geometry of quantum inference
Samuel L Braunstein · 1996
Earlier work this paper cites.
Mixed-state entanglement and distillation: Is there a “bound” entanglement in nature?
Michał Horodecki, Paweł Horodecki, and Ryszard Horodecki · 1998
Earlier work this paper cites.
Volume of the set of separable states
Karol Życzkowski, Paweł Horodecki, Anna Sanpera, and Maciej Lewenstein · 1998
Earlier work this paper cites.
Sequential minimal optimization: A fast algorithm for training support vector machines
John Platt · 1998
Earlier work this paper cites.
Bound entanglement can be activated
Paweł Horodecki, Michał Horodecki, and Ryszard Horodecki · 1999
Earlier work this paper cites.
Unextendible product bases and bound entanglement
Charles H. Bennett, David P. DiVincenzo, Tal Mor, Peter W. Shor, John A. Smolin, and Barbara M. Terhal · 1999
Earlier work this paper cites.
Robustness of entanglement
Guifré Vidal and Rolf Tarrach · 1999
Earlier work this paper cites.
Quantum Computation and Quantum Information
M. Nielsen and I. Chuang · 2000
Earlier work this paper cites.
Optimization of entanglement witnesses
Maciej Lewenstein, B Kraus, JI Cirac, and P Horodecki · 2000
Earlier work this paper cites.
An introduction to support vector machines and other kernel-based learning methods
Nello Cristianini, John Shawe-Taylor, et al · 2000
Earlier work this paper cites.
Experimental realization of shor’s quantum factoring algorithm using nuclear magnetic resonance
Lieven MK Vandersypen, Matthias Steffen, Gregory Breyta, Costantino S Yannoni, Mark H Sherwood, and Isaac L Chuang · 2001
Earlier work this paper cites.
Induced measures in the space of mixed quantum states
Karol Zyczkowski and Hans-Jürgen Sommers · 2001
Earlier work this paper cites.
Separability of n-particle mixed states: necessary and sufficient conditions in terms of linear maps
Michał Horodecki, Paweł Horodecki, and Ryszard Horodecki · 2001
Earlier work this paper cites.
Characterization of separable states and entanglement witnesses
Maciej Lewenstein, B Kraus, P Horodecki, and JI Cirac · 2001
Earlier work this paper cites.
Experimental two-photon, three-dimensional entanglement for quantum communication
Alipasha Vaziri, Gregor Weihs, and Anton Zeilinger · 2002
Cited alongside, same era.
Detection of entanglement with few local measurements
O Gühne, P Hyllus, D Bruß, A Ekert, M Lewenstein, C Macchiavello, and A Sanpera · 2002
Cited alongside, same era.
Superactivation of bound entanglement
Peter W. Shor, John A. Smolin, and Ashish V. Thapliyal · 2003
Cited alongside, same era.
Classical deterministic complexity of edmonds’ problem and quantum entanglement
Leonid Gurvits · 2003
Cited alongside, same era.
Generalized robustness of entanglement
Michael Steiner · 2003
Cited alongside, same era.
Hilbert–schmidt volume of the set of mixed quantum states
Karol Zyczkowski and Hans-Jürgen Sommers · 2003
Cited alongside, same era.
Generating random density matrices
Karol Życzkowski, Karol A Penson, Ion Nechita, and Benoit Collins · 2011
Later among the works it cites.
Regression as classification
Raied Salman and Vojislav Kecman · 2012
Later among the works it cites.
Efficient and robust automated machine learning
Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum, and Frank Hutter · 2015
Later among the works it cites.
Xgboost: extreme gradient boosting
Tianqi Chen, Tong He, Michael Benesty, Vadim Khotilovich, and Yuan Tang · 2015
Later among the works it cites.
Quantitative bound entanglement in two-qutrit states
Gael Sentís, Christopher Eltschka, and Jens Siewert · 2016
Later among the works it cites.
Deep Learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Nonlinear regression. hoboken
George AF Seber and Christopher John Wild · 2003
Cited alongside, same era.
Classical complexity and quantum entanglement
Leonid Gurvits · 2004
Cited alongside, same era.
Statistical properties of random density matrices
Hans-Jürgen Sommers and Karol Życzkowski · 2004
Cited alongside, same era.
Separable multipartite mixed states: operational asymptotically necessary and sufficient conditions
Fernando GSL Brandao and Reinaldo O Vianna · 2004
Cited alongside, same era.
Complete family of separability criteria
Andrew C. Doherty, Pablo A. Parrilo, and Federico M. Spedalieri · 2004
Cited alongside, same era.
Quantifying entanglement with witness operators
Fernando G. S. L. Brandão · 2005
Cited alongside, same era.
Tomography and generative training with quantum boltzmann machines
Mária Kieferová and Nathan Wiebe · 2017
Later among the works it cites.
Neural decoder for topological codes
Giacomo Torlai and Roger G. Melko · 2017
Later among the works it cites.
Deep neural network probabilistic decoder for stabilizer codes
Stefan Krastanov and Liang Jiang · 2017
Later among the works it cites.
Using recurrent neural networks to optimize dynamical decoupling for quantum memory
Moritz August and Xiaotong Ni · 2017
Later among the works it cites.
Machine learning & artificial intelligence in the quantum domain: a review of recent progress
Vedran Dunjko and Hans J Briegel · 2018
Later among the works it cites.
Neural-network quantum state tomography
Giacomo Torlai, Guglielmo Mazzola, Juan Carrasquilla, Matthias Troyer, Roger Melko, and Giuseppe Carleo · 2018
Later among the works it cites.
Experimental machine learning of quantum states
Jun Gao, Lu-Feng Qiao, Zhi-Qiang Jiao, Yue-Chi Ma, Cheng-Qiu Hu, Ruo-Jing Ren, Ai-Lin Yang, Hao Tang, Man-Hong Yung, and Xian-Min Jin · 2018
Later among the works it cites.
Separability-entanglement classifier via machine learning
Sirui Lu, Shilin Huang, Keren Li, Jun Li, Jianxin Chen, Dawei Lu, Zhengfeng Ji, Yi Shen, Duanlu Zhou, and Bei Zeng · 2018
Later among the works it cites.
Towards automatically-tuned deep neural networks
Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Matthias Urban, Michael Burkart, Max Dippel, Marius Lindauer, and Frank Hutter · 2018
Later among the works it cites.
Experimental simultaneous learning of multiple nonclassical correlations
Mu Yang, Chang liang Ren, Yue chi Ma, Ya Xiao, Xiang-Jun Ye, Lu-Lu Song, Jin-Shi Xu, Man-Hong Yung, Chuan-Feng Li, and Guang-Can Guo · 2019
Later among the works it cites.
Machine learning nonlocal correlations
Askery Canabarro, Samuraí Brito, and Rafael Chaves · 2019
Later among the works it cites.
Unveiling phase transitions with machine learning
Askery Canabarro, Felipe Fernandes Fanchini, André Luiz Malvezzi, Rodrigo Pereira, and Rafael Chaves · 2019
Later among the works it cites.
Scaling tree-based automated machine learning to biomedical big data with a feature set selector
TT Le, W Fu, and JH Moore · 2019
Later among the works it cites.
Auto-keras: An efficient neural architecture search system
Haifeng Jin, Qingquan Song, and Xia Hu · 2019
Later among the works it cites.
Analysis of the AutoML Challenge Series 2015–2018
Isabelle Guyon, Lisheng Sun-Hosoya, Marc Boullé, Hugo Jair Escalante, Sergio Escalera, Zhengying Liu, Damir Jajetic, Bisakha Ray, Mehreen Saeed, Michèle Sebag, Alexander Statnikov, Wei-Wei Tu, and Evelyne Viegas · 2019
Later among the works it cites.
A high-bias, low-variance introduction to machine learning for physicists
Pankaj Mehta, Marin Bukov, Ching-Hao Wang, Alexandre G.R. Day, Clint Richardson, Charles K. Fisher, and David J. Schwab · 2019
Later among the works it cites.