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

@inproceedings{aaai2021_informer_787,
  title = {{Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/11106-informer-beyond-efficient-transformer-for-long-sequence-time-series-forecasting/},
}

@inproceedings{neurips2019_enhancing_58216,
  title = {{Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13662},
}

@inproceedings{aaai2023_nhits_4225,
  title = {{NHITS: Neural Hierarchical Interpolation for Time Series Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25854},
}

@inproceedings{iclr2024_itransformer_34142,
  title = {{iTransformer: Inverted Transformers Are Effective for Time Series Forecasting}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18933},
}

@inproceedings{neurips2022_non_66279,
  title = {{Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55235},
}

@inproceedings{neurips2024_timexer_71490,
  title = {{TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95770},
}

@inproceedings{neurips2020_adversarial_59347,
  title = {{Adversarial Sparse Transformer for Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17376},
}

@inproceedings{neurips2022_earthformer_65877,
  title = {{Earthformer: Exploring Space-Time Transformers for Earth System Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54523},
}

@inproceedings{neurips2019_think_59081,
  title = {{Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13630},
}

@inproceedings{aaai2024_master_6564,
  title = {{MASTER: Market-Guided Stock Transformer for Stock Price Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27767},
}

@inproceedings{icml2019_deep_37274,
  title = {{Deep Factors for Forecasting}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3881},
}

@inproceedings{aaai2025_adaptive_8037,
  title = {{Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33908},
}

@inproceedings{aaai2024_stockmixer_7420,
  title = {{StockMixer: A Simple Yet Strong MLP-Based Architecture for Stock Price Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28681},
}

@inproceedings{aaai2024_u_7665,
  title = {{U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29337},
}

@inproceedings{iclr2023_scaleformer_33267,
  title = {{Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11535},
}

@inproceedings{iclr2024_pathformer_35135,
  title = {{Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17938},
}

@inproceedings{neurips2024_filternet_74301,
  title = {{FilterNet: Harnessing Frequency Filters for Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93257},
}

@inproceedings{neurips2024_ddn_72173,
  title = {{DDN: Dual-domain Dynamic Normalization for Non-stationary Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95167},
}

@inproceedings{neurips2024_frequency_72282,
  title = {{Frequency Adaptive Normalization For Non-stationary Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95063},
}

@inproceedings{aaai2025_amplifier_8096,
  title = {{Amplifier: Bringing Attention to Neglected Low-Energy Components in Time Series Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33267},
}

@inproceedings{iclr2025_fredf_80737,
  title = {{FreDF: Learning to Forecast in the Frequency Domain}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31031},
}

@inproceedings{neurips2024_scaling_72817,
  title = {{Scaling transformer neural networks for skillful and reliable medium-range weather forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94582},
}

@inproceedings{neurips2024_deformabletst_70985,
  title = {{DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96221},
}

@inproceedings{neurips2024_ada_72163,
  title = {{Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95175},
}

@inproceedings{neurips2024_rethinking_71209,
  title = {{Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96026},
}

@inproceedings{aaai2025_stem_10645,
  title = {{STEM-LTS: Integrating Semantic-Temporal Dynamics in LLM-driven Time Series Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34447},
}

@inproceedings{neurips2024_introducing_73125,
  title = {{Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94305},
}

@inproceedings{neurips2024_elastst_74294,
  title = {{ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93264},
}

@inproceedings{aaai2024_automixer_5231,
  title = {{AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30336},
}