% Key papers for Tensor network decompositions (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2016_supervised_56026,
  title = {{Supervised Learning with Tensor Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7064},
}

@inproceedings{aaai2021_fully_639,
  title = {{Fully-Connected Tensor Network Decomposition and Its Application to Higher-Order Tensor Completion}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/11071-fully-connected-tensor-network-decomposition-and-its-application-to-higher-order-tensor-completion/},
}

@inproceedings{iclr2020_tensor_29812,
  title = {{Tensor Decompositions for Temporal Knowledge Base Completion}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=rke2P1BFwS},
}

@inproceedings{icml2016_polynomial_35951,
  title = {{Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/blondel16.html},
}

@inproceedings{icml2018_canonical_36565,
  title = {{Canonical Tensor Decomposition for Knowledge Base Completion}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2246},
}

@inproceedings{neurips2021_scalars_62077,
  title = {{Scalars are universal: Equivariant machine learning, structured like classical physics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26367},
}

@inproceedings{neurips2018_computing_56956,
  title = {{Computing Higher Order Derivatives of Matrix and Tensor Expressions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11282},
}

@inproceedings{aaai2020_a_102019,
  title = {{A Simple and Efficient Tensor Calculus}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5881},
}

@inproceedings{neurips2019_crowdsourcing_58071,
  title = {{Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13862},
}

@inproceedings{aaai2022_random_2608,
  title = {{Random Tensor Theory for Tensor Decomposition}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/07913-random-tensor-theory-for-tensor-decomposition/},
}

@inproceedings{icml2019_on_37612,
  title = {{On the Universality of Invariant Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3813},
}

@inproceedings{neurips2017_scalable_56649,
  title = {{Scalable Demand-Aware Recommendation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9028},
}

@inproceedings{icml2017_tensor_36420,
  title = {{Tensor Belief Propagation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/651},
}

@inproceedings{aaai2020_nonlinear_102006,
  title = {{Nonlinear System Identification via Tensor Completion}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5868},
}

@inproceedings{icml2017_tensor_36422,
  title = {{Tensor Decomposition with Smoothness}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/556},
}

@inproceedings{neurips2017_tensor_56710,
  title = {{Tensor Biclustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8923},
}

@inproceedings{neurips2022_tensor_64216,
  title = {{Tensor Wheel Decomposition and Its Tensor Completion Application}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55368},
}

@inproceedings{cvpr2024_hdqmf_23654,
  title = {{HDQMF: Holographic Feature Decomposition Using Quantum Algorithms}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30748},
}

@inproceedings{iclr2019_learning_28888,
  title = {{Learning Two-layer Neural Networks with Symmetric Inputs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/872},
}

@inproceedings{iclr2023_constructive_33405,
  title = {{Constructive TT-representation of the tensors given as index interaction functions with applications}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11751},
}

@inproceedings{neurips2024_generalized_70245,
  title = {{Generalized Tensor Decomposition for Understanding Multi-Output Regression under Combinatorial Shifts}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96844},
}

@inproceedings{aaai2025_tensor_10948,
  title = {{Tensor Decomposition Meets Knowledge Compilation: A Study Comparing Tensor Trains with OBDDs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33657},
}

@inproceedings{icml2025_tensor_46524,
  title = {{Tensor Product Neural Networks for Functional ANOVA Model}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46044},
}

@inproceedings{icml2025_the_46654,
  title = {{The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45917},
}

@inproceedings{icml2025_permutation_48473,
  title = {{Permutation Equivariant Neural Networks for Symmetric Tensors}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44145},
}

@inproceedings{icml2026_grokking_49727,
  title = {{Grokking Finite-Dimensional Algebra}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=5Cvh976L09},
}

@inproceedings{icml2026_asymptotically_50041,
  title = {{Asymptotically Fast Clebsch-Gordan Tensor Products with Vector Spherical Harmonics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=8UzZ0CbPsk},
}

@inproceedings{neurips2025_towards_74759,
  title = {{Towards a Geometric Understanding of Tensor Learning via the t-Product}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=0uo2GPd94f},
}

@inproceedings{iclr2026_it_86524,
  title = {{It's All Just Vectorization: einx, a Universal Notation for Tensor Operations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=QqvQ3iAdpC},
}

@inproceedings{icml2025_low_48222,
  title = {{Low-Rank Tensor Transitions (LoRT) for Transferable Tensor Regression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44389},
}

@inproceedings{icml2026_refining_49341,
  title = {{Refining Dual Spectral Sparsity in Transformed Tensor Singular Values}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=1ZIjW3LFcH},
}

@inproceedings{neurips2026_recipe_91272,
  title = {{RECIPE: Learning to Rank Complete Precursor Sets for Inorganic Retrosynthesis}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149027},
}