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

@inproceedings{icml2018_accurate_36492,
  title = {{Accurate Uncertainties for Deep Learning Using Calibrated Regression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2486},
}

@inproceedings{neurips2016_temporal_56033,
  title = {{Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6916},
}

@inproceedings{aaai2019_robuststl_101765,
  title = {{RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4480},
}

@inproceedings{aaai2016_data_105065,
  title = {{Data Poisoning Attacks against Autoregressive Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10237},
}

@inproceedings{aaai2020_riskoracle_100307,
  title = {{RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5480},
}

@inproceedings{aaai2022_reinforcement_2630,
  title = {{Reinforcement Learning Based Dynamic Model Combination for Time Series Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/06639-reinforcement-learning-based-dynamic-model-combination-for-time-series-forecasting/},
}

@inproceedings{neurips2020_interpretable_60099,
  title = {{Interpretable Sequence Learning for Covid-19 Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/19069},
}

@inproceedings{neurips2021_revisiting_63257,
  title = {{Revisiting Time Series Outlier Detection: Definitions and Benchmarks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://openreview.net/forum?id=r8IvOsnHchr},
}

@inproceedings{aaai2021_sub_1440,
  title = {{Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/00169-sub-seasonal-climate-forecasting-via-machine-learning-challenges-analysis-and-advances/},
}

@inproceedings{aaai2021_learning_893,
  title = {{Learning Representations for Incomplete Time Series Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08837-learning-representations-for-incomplete-time-series-clustering/},
}

@inproceedings{aaai2021_steering_1421,
  title = {{Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04855-steering-a-historical-disease-forecasting-model-under-a-pandemic-case-of-flu-and-covid-19/},
}

@inproceedings{neurips2020_what_61101,
  title = {{What went wrong and when? Instance-wise feature importance for time-series black-box models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18759},
}

@inproceedings{aaai2017_regularization_104589,
  title = {{Regularization in Hierarchical Time Series Forecasting with Application to Electricity Smart Meter Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11167},
}

@inproceedings{aaai2019_estimating_101600,
  title = {{Estimating the Days to Success of Campaigns in Crowdfunding: A Deep Survival Perspective}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4295},
}

@inproceedings{aaai2021_complete_276,
  title = {{Complete Closed Time Intervals-Related Patterns Mining}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04098-complete-closed-time-intervals-related-patterns-mining/},
}

@inproceedings{aaai2018_distant_102409,
  title = {{Distant-Supervision of Heterogeneous Multitask Learning for Social Event Forecasting With Multilingual Indicators}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11676},
}

@inproceedings{neurips2024_motion_70470,
  title = {{Motion Forecasting in Continuous Driving}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96638},
}

@inproceedings{neurips2021_adjusting_63354,
  title = {{Adjusting for Autocorrelated Errors in Neural Networks for Time Series}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26808},
}

@inproceedings{icml2018_not_36882,
  title = {{Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2119},
}

@inproceedings{neurips2023_wildfirespreadts_68137,
  title = {{WildfireSpreadTS: A dataset of multi-modal time series for wildfire spread prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/73593},
}

@inproceedings{aaai2024_citypulse_5402,
  title = {{CityPulse: Fine-Grained Assessment of Urban Change with Street View Time Series}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30216},
}

@inproceedings{aaai2025_cherry_8415,
  title = {{Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34224},
}

@inproceedings{aaai2024_early_5788,
  title = {{Early Detection of Extreme Storm Tide Events Using Multimodal Data Processing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30194},
}

@inproceedings{aaai2025_droughtset_8817,
  title = {{DroughtSet: Understanding Drought Through Spatial-Temporal Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35066},
}

@inproceedings{neurips2024_scaling_71095,
  title = {{Scaling Law for Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96119},
}

@inproceedings{aaai2024_cgs_5338,
  title = {{CGS-Mask: Making Time Series Predictions Intuitive for All}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29325},
}

@inproceedings{iclr2024_contrastive_33462,
  title = {{Contrastive Difference Predictive Coding}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19613},
}

@inproceedings{iclr2024_robusttsf_35159,
  title = {{RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17914},
}

@inproceedings{icml2024_the_44357,
  title = {{The Merit of River Network Topology for Neural Flood Forecasting}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34095},
}

@inproceedings{icml2024_sibblings_45049,
  title = {{SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33403},
}

@inproceedings{neurips2024_off_71466,
  title = {{Off to new Shores: A Dataset \& Benchmark for (near-)coastal Flood Inundation Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97766},
}

@inproceedings{iclr2025_hr_80804,
  title = {{HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30964},
}

@inproceedings{iclr2026_tianquan_84831,
  title = {{TianQuan-S2S: A Subseasonal-to-Seasonal Global Weather Model via Incorporate Climatology State}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=7Dvmq7MhwU},
}

@inproceedings{aaai2026_beyond_107479,
  title = {{Beyond MSE: Ordinal Cross-Entropy for Probabilistic Time Series Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39831},
}

@inproceedings{aaai2025_gcf_9269,
  title = {{GCF: Estimating Unobserved Demand Using Graph Causal Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35148},
}

@inproceedings{aaai2025_hubness_9462,
  title = {{Hubness Change Point Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33376},
}

@inproceedings{icml2024_reservoir_43775,
  title = {{Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34677},
}

@inproceedings{icml2024_an_44269,
  title = {{An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34183},
}

@inproceedings{icml2025_capturing_48746,
  title = {{Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43876},
}