% Key papers for Time series representation learning (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2022_ts2vec_2808,
  title = {{TS2Vec: Towards Universal Representation of Time Series}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/08980-ts2vec-towards-universal-representation-of-time-series/},
}

@inproceedings{cvpr2024_unireplknet_25134,
  title = {{UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio Video Point Cloud Time-Series and Image Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29635},
}

@inproceedings{neurips2019_unsupervised_59159,
  title = {{Unsupervised Scalable Representation Learning for Multivariate Time Series}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13615},
}

@inproceedings{iclr2020_n_29742,
  title = {{N-BEATS: Neural basis expansion analysis for interpretable time series forecasting}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=r1ecqn4YwB},
}

@inproceedings{icml2017_soft_36397,
  title = {{Soft-DTW: a Differentiable Loss Function for Time-Series}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/769},
}

@inproceedings{neurips2022_self_64796,
  title = {{Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52895},
}

@inproceedings{aaai2024_timesurl_7567,
  title = {{TimesURL: Self-Supervised Contrastive Learning for Universal Time Series Representation Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29299},
}

@inproceedings{aaai2023_time_4817,
  title = {{Time Series Contrastive Learning with Information-Aware Augmentations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25575},
}

@inproceedings{iclr2022_cost_31250,
  title = {{CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6829},
}

@inproceedings{aaai2021_time_1512,
  title = {{Time Series Domain Adaptation via Sparse Associative Structure Alignment}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/06859-time-series-domain-adaptation-via-sparse-associative-structure-alignment/},
}

@inproceedings{iclr2017_variational_28374,
  title = {{Variational Recurrent Adversarial Deep Domain Adaptation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=rk9eAFcxg},
}

@inproceedings{iclr2022_omni_31239,
  title = {{Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/7148},
}

@inproceedings{cvpr2018_non_13427,
  title = {{Non-Linear Temporal Subspace Representations for Activity Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Cherian_Non-Linear_Temporal_Subspace_CVPR_2018_paper.html},
}

@inproceedings{aaai2023_mhccl_4112,
  title = {{MHCCL: Masked Hierarchical Cluster-Wise Contrastive Learning for Multivariate Time Series}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26098},
}

@inproceedings{cvpr2016_deep_11463,
  title = {{Deep Canonical Time Warping}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{aaai2024_ci_5341,
  title = {{CI-STHPAN: Pre-trained Attention Network for Stock Selection with Channel-Independent Spatio-Temporal Hypergraph}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28770},
}

@inproceedings{neurips2023_simmtm_69046,
  title = {{SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70829},
}

@inproceedings{iclr2021_unsupervised_30053,
  title = {{Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2897},
}

@inproceedings{icml2022_unsupervised_41324,
  title = {{Unsupervised Time-Series Representation Learning with Iterative Bilinear Temporal-Spectral Fusion}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16051},
}

@inproceedings{aaai2023_sensor_4575,
  title = {{SEnsor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26221},
}

@inproceedings{aaai2024_graph_6161,
  title = {{Graph-Aware Contrasting for Multivariate Time-Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29501},
}

@inproceedings{aaai2024_cross_5526,
  title = {{Cross-Domain Contrastive Learning for Time Series Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28740},
}

@inproceedings{aaai2024_simpsi_7342,
  title = {{SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29405},
}

@inproceedings{aaai2025_content_8515,
  title = {{Content-aware Balanced Spectrum Encoding in Masked Modeling for Time Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33875},
}

@inproceedings{iclr2024_learning_34600,
  title = {{Learning to Embed Time Series Patches Independently}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18474},
}

@inproceedings{aaai2025_frequency_9237,
  title = {{Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33828},
}

@inproceedings{aaai2026_mask_107425,
  title = {{Mask the Redundancy: Evolving Masking Representation Learning for Multivariate Time-Series Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39777},
}

@inproceedings{aaai2025_enhancing_8972,
  title = {{Enhancing Masked Time-Series Modeling via Dropping Patches}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34211},
}

@inproceedings{iclr2024_soft_35283,
  title = {{Soft Contrastive Learning for Time Series}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17790},
}

@inproceedings{neurips2024_boosting_72989,
  title = {{Boosting Transferability and Discriminability for Time Series Domain Adaptation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94429},
}

@inproceedings{aaai2024_towards_7586,
  title = {{Towards Diverse Perspective Learning with Selection over Multiple Temporal Poolings}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28743},
}

@inproceedings{aaai2025_clep_8345,
  title = {{CLEP: A Novel Contrastive Learning Method for Evolutionary Reentrancy Vulnerability Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/31981},
}

@inproceedings{aaai2025_enhancing_8979,
  title = {{Enhancing Multivariate Time-Series Domain Adaptation via Contrastive Frequency Graph Discovery and Language-Guided Adversary Alignment}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33863},
}

@inproceedings{iclr2024_t_33589,
  title = {{T-Rep: Representation Learning for Time Series using Time-Embeddings}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19486},
}

@inproceedings{neurips2024_segment_74660,
  title = {{Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/92935},
}

@inproceedings{aaai2025_a_7878,
  title = {{A Compact Implicit Neural Representation for Efficient Storage of Massive 4D Functional Magnetic Resonance Imaging}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32520},
}

@inproceedings{aaai2025_temporal_10944,
  title = {{Temporal Streaming Batch Principal Component Analysis for Time Series Classification (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35319},
}