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

@inproceedings{aaai2020_tapnet_102303,
  title = {{TapNet: Multivariate Time Series Classification with Attentional Prototypical Network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6165},
}

@inproceedings{aaai2021_shapenet_1381,
  title = {{ShapeNet: A Shapelet-Neural Network Approach for Multivariate Time Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08375-shapenet-a-shapelet-neural-network-approach-for-multivariate-time-series-classification/},
}

@inproceedings{neurips2019_learning_58502,
  title = {{Learning Representations for Time Series Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13544},
}

@inproceedings{cvpr2019_temporal_14903,
  title = {{Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{neurips2024_medformer_73538,
  title = {{Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93940},
}

@inproceedings{aaai2021_multi_1029,
  title = {{Multi-modal Multi-label Emotion Recognition with Heterogeneous Hierarchical Message Passing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/14338-multi-modal-multi-label-emotion-recognition-with-heterogeneous-hierarchical-message-passing/},
}

@inproceedings{aaai2023_temporal_4786,
  title = {{Temporal-Frequency Co-training for Time Series Semi-supervised Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26072},
}

@inproceedings{aaai2021_learnable_856,
  title = {{Learnable Dynamic Temporal Pooling for Time Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08288-learnable-dynamic-temporal-pooling-for-time-series-classification/},
}

@inproceedings{aaai2024_diffusion_5693,
  title = {{Diffusion Language-Shapelets for Semi-supervised Time-Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29317},
}

@inproceedings{aaai2020_adversarial_102086,
  title = {{Adversarial Dynamic Shapelet Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5948},
}

@inproceedings{aaai2023_primenet_4408,
  title = {{PrimeNet: Pre-training for Irregular Multivariate Time Series}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25876},
}

@inproceedings{neurips2018_learning_57302,
  title = {{Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11997},
}

@inproceedings{neurips2023_time_68617,
  title = {{Time Series as Images: Vision Transformer for Irregularly Sampled Time Series}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71219},
}

@inproceedings{neurips2021_hirid_62282,
  title = {{HiRID-ICU-Benchmark --- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://openreview.net/forum?id=SnC9rUeqiqd},
}

@inproceedings{aaai2021_correlative_332,
  title = {{Correlative Channel-Aware Fusion for Multi-View Time Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/06714-correlative-channel-aware-fusion-for-multi-view-time-series-classification/},
}

@inproceedings{aaai2021_joint_823,
  title = {{Joint-Label Learning by Dual Augmentation for Time Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08847-joint-label-learning-by-dual-augmentation-for-time-series-classification/},
}

@inproceedings{aaai2020_deep_100596,
  title = {{Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5497},
}

@inproceedings{icml2021_neighborhood_39653,
  title = {{Neighborhood Contrastive Learning Applied to Online Patient Monitoring}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9349},
}

@inproceedings{neurips2018_learning_57308,
  title = {{Learning filter widths of spectral decompositions with wavelets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11453},
}

@inproceedings{aaai2019_adversarial_100162,
  title = {{Adversarial Unsupervised Representation Learning for Activity Time-Series}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3870},
}

@inproceedings{aaai2024_audio_5224,
  title = {{Audio Scanning Network: Bridging Time and Frequency Domains for Audio Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29015},
}

@inproceedings{aaai2024_pharmacokinetics_6950,
  title = {{Pharmacokinetics-Informed Neural Network for Predicting Opioid Administration Moments with Wearable Sensors}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30326},
}

@inproceedings{aaai2024_self_7293,
  title = {{Self-Supervised Framework Based on Subject-Wise Clustering for Human Subject Time Series Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30240},
}

@inproceedings{aaai2025_hierarchical_9431,
  title = {{Hierarchical Classification Auxiliary Network for Time Series Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34286},
}

@inproceedings{aaai2024_energy_5837,
  title = {{Energy Efficient Streaming Time Series Classification with Attentive Power Iteration}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29151},
}

@inproceedings{aaai2025_integrating_9585,
  title = {{Integrating Sequence and Image Modeling in Irregular Medical Time Series Through Self-Supervised Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33737},
}

@inproceedings{icml2024_timemil_43708,
  title = {{TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34744},
}

@inproceedings{neurips2024_advancing_73592,
  title = {{Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93894},
}

@inproceedings{aaai2025_language_9702,
  title = {{Language Pre-training Guided Masking Representation Learning for Time Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33377},
}

@inproceedings{aaai2025_scalable_10674,
  title = {{Scalable Hierarchical Deep Neural Network for Time Series Analysis in Wearable Sensor-based Human Activity Recognition}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35206},
}

@inproceedings{iclr2024_inherently_35631,
  title = {{Inherently Interpretable Time Series Classification via Multiple Instance Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17442},
}

@inproceedings{neurips2024_con4m_73503,
  title = {{Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93973},
}

@inproceedings{iclr2025_learning_80835,
  title = {{Learning under Temporal Label Noise}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30932},
}

@inproceedings{iclr2025_reading_80870,
  title = {{Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30897},
}

@inproceedings{aaai2026_edgemtsc_106386,
  title = {{EdgeMTSC: A Lightweight Large-Kernel ConvNet for Multivariate Time Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38693},
}

@inproceedings{aaai2025_aligning_8082,
  title = {{Aligning Time-series by Local Trends: Applications in Public Health}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35062},
}

@inproceedings{aaai2025_intedisux_9578,
  title = {{InteDisUX: Intepretation-Guided Discriminative User-Centric Explanation for Time Series}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35387},
}

@inproceedings{icml2025_learning_46435,
  title = {{Learning Soft Sparse Shapes for Efficient Time-Series Classification}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46130},
}