[9] Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, and Shandian Zhe. Streaming bayesian deep tensor factorization. In International Conference on Machine Learning, pages 3133-3142. PMLR, 2021.
[10] Ivan Glasser, Ryan Sweke, Nicola Pancotti, Jens Eisert, and Ignacio Cirac. Expressive power of tensor-network factorizations for probabilistic modeling. Advances in neural information processing systems, 32, 2019.
[11] Michael Gutmann and Aapo Hyvarinen. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. In Proceedings of the thirteenth international conference on artificial intelligence and statistics, pages 297–304. JMLR Workshop and Conference Proceedings, 2010.
[12] Zhi Han, Yao Wang, Qian Zhao, Deyu Meng, Lin Lin, Yandong Tang, et al. A generalized model for robust tensor factorization with noise modeling by mixture of gaussians. IEEE transactions on neural networks and learning systems, 29(11):5380-5393, 2018.
[13] Kohei Hayashi, Takashi Takenouchi, Tomohiro Shibata, Yuki Kamiya, Daishi Kato, Kazuo Kunieda, Keiji Yamada, and Kazushi Ikeda. Exponential family tensor factorization for missing-values prediction and anomaly detection. In 2010 IEEE International Conference on Data Mining, pages 216-225. IEEE, 2010.
[14] Geoffrey E Hinton. Training products of experts by minimizing contrastive divergence. Neural computation, 14(8):1771-1800, 2002.
[15] Frank L Hitchcock. The expression of a tensor or a polyadic as a sum of products. Journal of Mathematics and Physics, 6(1-4):164-189, 1927.
[16] Aapo Hyvärinen and Peter Dayan. Estimation of non-normalized statistical models by score matching. Journal of Machine Learning Research, 6(4), 2005.
[17] Diederik P Kingma and Jimmy Ba. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980, 2014.
[18] Diederik P Kingma and Max Welling. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114, 2013.
[19] Tamara G Kolda and Brett W Bader. Tensor decompositions and applications. SIAM review, 51(3):455-500, 2009.
[20] Maxim Kuznetsov, Daniil Polykovskiy, Dmitry P Vetrov, and Alex Zhebrak. A prior of a googol gaussians: a tensor ring induced prior for generative models. Advances in Neural Information Processing Systems, 32, 2019.
[21] Yann LeCun, Sumit Chopra, Raia Hadsell, M Ranzato, and Fujie Huang. A tutorial on energy-based learning. Predicting structured data, 1(0), 2006.
[22] Chao Li and Zhun Sun. Evolutionary topology search for tensor network decomposition. In International Conference on Machine Learning, pages 5947-5957. PMLR, 2020.
[23] Chao Li, Junhua Zeng, Zerui Tao, and Qibin Zhao. Permutation search of tensor network structures via local sampling. In International Conference on Machine Learning, pages 13106-13124. PMLR, 2022.
[24] Shibo Li, Robert Kirby, and Shandian Zhe. Decomposing temporal high-order interactions via latent ODEs. In Proceedings of the 39th International Conference on Machine Learning, volume 162 of Proceedings of Machine Learning Research, pages 12797-12812. PMLR, 2022.
[25] Hanpeng Liu, Yaguang Li, Michael Tsang, and Yan Liu. Costco: A neural tensor completion model for sparse tensors. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pages 324-334, 2019.
[26] Zhen Long, Ce Zhu, Jiani Liu, and Yipeng Liu. Bayesian low rank tensor ring for image recovery. IEEE Transactions on Image Processing, 30:3568-3580, 2021.