@article{penrose1971applications,
  title={Applications of negative dimensional tensors},
  author={Penrose, Roger},
  journal={Combinatorial mathematics and its applications},
  volume={1},
  pages={221--244},
  year={1971}
}
@article{lippmann1987introduction,
  title={An introduction to computing with neural nets},
  author={Lippmann, Richard},
  journal={IEEE Assp magazine},
  volume={4},
  number={2},
  pages={4--22},
  year={1987},
  publisher={IEEE}
}
@inproceedings{boser1992training,
  title={A training algorithm for optimal margin classifiers},
  author={Boser, Bernhard E and Guyon, Isabelle M and Vapnik, Vladimir N},
  booktitle={Proceedings of the fifth annual workshop on Computational learning theory},
  pages={144--152},
  year={1992}
}

@article{cortes1995support,
  title={Support-vector networks},
  author={Cortes, Corinna and Vapnik, Vladimir},
  journal={Machine learning},
  volume={20},
  number={3},
  pages={273--297},
  year={1995},
  publisher={Springer}
}
@article{burges1998tutorial,
  title={A tutorial on support vector machines for pattern recognition},
  author={Burges, Christopher JC},
  journal={Data mining and knowledge discovery},
  volume={2},
  number={2},
  pages={121--167},
  year={1998},
  publisher={Springer}
}
@article{koenderink1999structure,
  title={The structure of locally orderless images},
  author={Koenderink, Jan J and Van Doorn, Andrea J},
  journal={International Journal of Computer Vision},
  volume={31},
  number={2-3},
  pages={159--168},
  year={1999},
  publisher={Springer}
}
@article{armato2004lung,
  title={Lung image database consortium: developing a resource for the medical imaging research community},
  author={Armato III, Samuel G and McLennan, Geoffrey and McNitt-Gray, Michael F and Meyer, Charles R and Yankelevitz, David and Aberle, Denise R and Henschke, Claudia I and Hoffman, Eric A and Kazerooni, Ella A and MacMahon, Heber and others},
  journal={Radiology},
  volume={232},
  number={3},
  pages={739--748},
  year={2004},
  publisher={Radiological Society of North America}
}
@article{shi2006classical,
  title={Classical simulation of quantum many-body systems with a tree tensor network},
  author={Shi, Y-Y and Duan, L-M and Vidal, Guifre},
  journal={Physical review a},
  volume={74},
  number={2},
  pages={022320},
  year={2006},
  publisher={APS}
}
@article{cichocki2016tensor,
  title={Tensor networks for dimensionality reduction and large-scale optimization: Part 1 low-rank tensor decompositions},
  author={Cichocki, Andrzej and Lee, Namgil and Oseledets, Ivan and Phan, Anh-Huy and Zhao, Qibin and Mandic, Danilo P and others},
  journal={Foundations and Trends{\textregistered} in Machine Learning},
  volume={9},
  number={4-5},
  pages={249--429},
  year={2016},
  publisher={Now Publishers, Inc.}
}
@article{lecun2015deep,
  title={Deep learning},
  author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
  journal={nature},
  volume={521},
  number={7553},
  pages={436--444},
  year={2015},
  publisher={Nature Publishing Group}
}

@article{bordes2005fast,
  title={Fast kernel classifiers with online and active learning},
  author={Bordes, Antoine and Ertekin, Seyda and Weston, Jason and Bottou, L{\'e}on},
  journal={Journal of Machine Learning Research},
  volume={6},
  number={Sep},
  pages={1579--1619},
  year={2005}
}
@article{verstraete2004renormalization,
  title={Renormalization algorithms for quantum-many body systems in two and higher dimensions},
  author={Verstraete, Frank and Cirac, J Ignacio},
  journal={arXiv preprint cond-mat/0407066},
  year={2004}
}
@article{hofmann2008kernel,
  title={Kernel methods in machine learning},
  author={Hofmann, Thomas and Sch{\"o}lkopf, Bernhard and Smola, Alexander J},
  journal={The annals of statistics},
  pages={1171--1220},
  year={2008},
  publisher={JSTOR}
}
@article{schollwock2005density,
  title={The density-matrix renormalization group},
  author={Schollw{\"o}ck, Ulrich},
  journal={Reviews of modern physics},
  volume={77},
  number={1},
  pages={259},
  year={2005},
  publisher={APS}
}

@article{perez2006matrix,
  title={Matrix product state representations},
  author={Perez-Garcia, David and Verstraete, Frank and Wolf, Michael M and Cirac, J Ignacio},
  journal={arXiv preprint quant-ph/0608197},
  year={2006}
}
@article{kingma2014adam,
  title={Adam: A method for stochastic optimization},
  author={Kingma, Diederik P and Ba, Jimmy},
  journal={arXiv preprint arXiv:1412.6980},
  year={2014}
}

@article{oseledets2011tensor,
  title={Tensor-train decomposition},
  author={Oseledets, Ivan V},
  journal={SIAM Journal on Scientific Computing},
  volume={33},
  number={5},
  pages={2295--2317},
  year={2011},
  publisher={SIAM}
}

@inproceedings{novikov2015tensorizing,
  title={Tensorizing neural networks},
  author={Novikov, Alexander and Podoprikhin, Dmitrii and Osokin, Anton and Vetrov, Dmitry P},
  booktitle={Advances in neural information processing systems},
  pages={442--450},
  year={2015}
}


@inproceedings{stoudenmire2016supervised,
  title={Supervised learning with tensor networks},
  author={Stoudenmire, Edwin and Schwab, David J},
  booktitle={Advances in Neural Information Processing Systems},
  pages={4799--4807},
  year={2016}
}
@article{bejnordi2017diagnostic,
  title={Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer},
  author={Bejnordi, Babak Ehteshami and Veta, Mitko and Van Diest, Paul Johannes and Van Ginneken, Bram and Karssemeijer, Nico and Litjens, Geert and Van Der Laak, Jeroen AWM and Hermsen, Meyke and Manson, Quirine F and Balkenhol, Maschenka and others},
  journal={Jama},
  volume={318},
  number={22},
  pages={2199--2210},
  year={2017},
  publisher={American Medical Association}
}
@article{novikov2016exponential,
  title={Exponential machines},
  author={Novikov, Alexander and Trofimov, Mikhail and Oseledets, Ivan},
  journal={arXiv preprint arXiv:1605.03795},
  year={2016}
}
@article{bridgeman2017hand,
  title={Hand-waving and interpretive dance: an introductory course on tensor networks},
  author={Bridgeman, Jacob C and Chubb, Christopher T},
  journal={Journal of Physics A: Mathematical and Theoretical},
  volume={50},
  number={22},
  pages={223001},
  year={2017},
  publisher={IOP Publishing}
}

@inproceedings{cohen2016expressive,
  title={On the expressive power of deep learning: A tensor analysis},
  author={Cohen, Nadav and Sharir, Or and Shashua, Amnon},
  booktitle={Conference on Learning Theory},
  pages={698--728},
  year={2016}
}
@inproceedings{khrulkov2017expressive,
  title={Expressive power of recurrent neural networks},
  author={Khrulkov, Valentin and Novikov, Alexander and Oseledets, Ivan},
  booktitle={Conference on Learning Theory},
  year={2018}
}
@inproceedings{rhu2016vdnn,
  title={vDNN: Virtualized deep neural networks for scalable, memory-efficient neural network design},
  author={Rhu, Minsoo and Gimelshein, Natalia and Clemons, Jason and Zulfiqar, Arslan and Keckler, Stephen W},
  booktitle={2016 49th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)},
  pages={1--13},
  year={2016},
  organization={IEEE}
}
@inproceedings{dinh2016density,
  title={Density estimation using {R}eal {NVP}},
  author={Dinh, Laurent and Sohl-Dickstein, Jascha and Bengio, Samy},
  booktitle={International Conference on Learning Representation},
  year={2017}
}
@inproceedings{huang2017densely,
  title={Densely connected convolutional networks},
  author={Huang, Gao and Liu, Zhuang and Van Der Maaten, Laurens and Weinberger, Kilian Q},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={4700--4708},
  year={2017}
}
@inproceedings{veeling2018rotation,
  title={Rotation equivariant {CNN}s for digital pathology},
  author={Veeling, Bastiaan S and Linmans, Jasper and Winkens, Jim and Cohen, Taco and Welling, Max},
  booktitle={International Conference on Medical image computing and computer-assisted intervention},
  pages={210--218},
  year={2018},
  organization={Springer}
}
@inproceedings{kohl2018probabilistic,
  title={A probabilistic u-net for segmentation of ambiguous images},
  author={Kohl, Simon and Romera-Paredes, Bernardino and Meyer, Clemens and De Fauw, Jeffrey and Ledsam, Joseph R and Maier-Hein, Klaus and Eslami, SM Ali and Rezende, Danilo Jimenez and Ronneberger, Olaf},
  booktitle={Advances in Neural Information Processing Systems},
  pages={6965--6975},
  year={2018}
}
@inproceedings{baumgartner2019phiseg,
  title={Phiseg: Capturing uncertainty in medical image segmentation},
  author={Baumgartner, Christian F and Tezcan, Kerem C and Chaitanya, Krishna and H{\"o}tker, Andreas M and Muehlematter, Urs J and Schawkat, Khoschy and Becker, Anton S and Donati, Olivio and Konukoglu, Ender},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={119--127},
  year={2019},
  organization={Springer}
}
@misc{lidc,
  author = {Knegt, Stefan},
  title = {A {P}robabilistic {U-N}et for segmentation of ambiguous images implemented in {P}y{T}orch},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/stefanknegt/Probabilistic-Unet-Pytorch}},
}


@misc{torchmps,
  author = {Miller, Jacob},
  title = {TorchMPS},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/jemisjoky/torchmps}},
}

@article{efthymiou2019tensornetwork,
  title={TensorNetwork for {M}achine {L}earning},
  author={Efthymiou, Stavros and Hidary, Jack and Leichenauer, Stefan},
  journal={arXiv preprint arXiv:1906.06329},
  year={2019}
}
@article{liu2019machine,
  title={Machine learning by unitary tensor network of hierarchical tree structure},
  author={Liu, Ding and Ran, Shi-Ju and Wittek, Peter and Peng, Cheng and Garc{\'\i}a, Raul Bl{\'a}zquez and Su, Gang and Lewenstein, Maciej},
  journal={New Journal of Physics},
  volume={21},
  number={7},
  pages={073059},
  year={2019},
  publisher={IOP Publishing}
}
@article{han2018unsupervised,
  title={Unsupervised generative modeling using matrix product states},
  author={Han, Zhao-Yu and Wang, Jun and Fan, Heng and Wang, Lei and Zhang, Pan},
  journal={Physical Review X},
  volume={8},
  number={3},
  pages={031012},
  year={2018},
  publisher={APS}
}
@inproceedings{glasser2019expressive,
  title={Expressive power of tensor-network factorizations for probabilistic modeling},
  author={Glasser, Ivan and Sweke, Ryan and Pancotti, Nicola and Eisert, Jens and Cirac, Ignacio},
  booktitle={Advances in Neural Information Processing Systems},
  pages={1496--1508},
  year={2019}
}
@inproceedings{paszke2019pytorch,
  title={PyTorch: An imperative style, high-performance deep learning library},
  author={Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
  booktitle={Advances in Neural Information Processing Systems},
  pages={8024--8035},
  year={2019}
}
@article{klus2019tensor,
  title={Tensor-based algorithms for image classification},
  author={Klus, Stefan and Gel{\ss}, Patrick},
  journal={Algorithms},
  volume={12},
  number={11},
  pages={240},
  year={2019},
  publisher={Multidisciplinary Digital Publishing Institute}
}
