% Key papers for Neural point-process models (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_the_56719,
  title = {{The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9443},
}

@inproceedings{cvpr2020_event_15494,
  title = {{Event Probability Mask (EPM) and Event Denoising Convolutional Neural Network (EDnCNN) for Neuromorphic Cameras}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2021_clinical_254,
  title = {{Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/14647-clinical-temporal-relation-extraction-with-probabilistic-soft-logic-regularization-and-global-inference/},
}

@inproceedings{icml2016_isotonic_35875,
  title = {{Isotonic Hawkes Processes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/wangg16.html},
}

@inproceedings{icml2017_uncovering_36438,
  title = {{Uncovering Causality from Multivariate Hawkes Integrated Cumulants}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/673},
}

@inproceedings{aaai2018_learning_100343,
  title = {{Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11307},
}

@inproceedings{icml2016_bayesian_35752,
  title = {{Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/schein16.html},
}

@inproceedings{aaai2019_safe_100215,
  title = {{SAFE: A Neural Survival Analysis Model for Fraud Early Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3923},
}

@inproceedings{icml2017_learning_36254,
  title = {{Learning Hawkes Processes from Short Doubly-Censored Event Sequences}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/543},
}

@inproceedings{aaai2018_hawkes_103369,
  title = {{Hawkes Process Inference With Missing Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/12116},
}

@inproceedings{icml2017_isurvive_36463,
  title = {{iSurvive: An Interpretable, Event-time Prediction Model for mHealth}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/732},
}

@inproceedings{icml2017_learning_36262,
  title = {{Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/573},
}

@inproceedings{aaai2020_a_99747,
  title = {{A Variational Point Process Model for Social Event Sequences}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5348},
}

@inproceedings{neurips2018_modelling_57389,
  title = {{Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11244},
}

@inproceedings{aaai2016_the_105078,
  title = {{The Ostomachion Process}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10250},
}

@inproceedings{neurips2018_stochastic_57656,
  title = {{Stochastic Nonparametric Event-Tensor Decomposition}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11661},
}

@inproceedings{neurips2019_meta_58589,
  title = {{Meta Learning with Relational Information for Short Sequences}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14016},
}

@inproceedings{icml2019_imputing_37446,
  title = {{Imputing Missing Events in Continuous-Time Event Streams}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3675},
}

@inproceedings{aaai2023_concurrent_3304,
  title = {{Concurrent Multi-Label Prediction in Event Streams}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26172},
}

@inproceedings{icml2016_hierarchical_35865,
  title = {{Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/adams16.html},
}

@inproceedings{aaai2025_geomamba_9336,
  title = {{GeoMamba: Towards Multi-granular POI Recommendation with Geographical State Space Model}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33360},
}

@inproceedings{aaai2024_a_5082,
  title = {{A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29570},
}

@inproceedings{aaai2024_discovering_5705,
  title = {{Discovering Sequential Patterns with Predictable Inter-event Delays}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28676},
}

@inproceedings{neurips2024_pplns_72215,
  title = {{PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95126},
}

@inproceedings{aaai2025_deep_8681,
  title = {{Deep Representation Learning for Forecasting Recursive and Multi-Relational Events in Temporal Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33857},
}

@inproceedings{neurips2024_unscrambling_72268,
  title = {{Unscrambling disease progression at scale: fast inference of event permutations with optimal transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95076},
}

@inproceedings{iclr2024_amortized_33755,
  title = {{Amortized Network Intervention to Steer the Excitatory Point Processes}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19320},
}

@inproceedings{icml2026_marrying_50131,
  title = {{Marrying Generative Model of Healthcare Events with Digital Twin of Social Determinants of Health for Disease Reasoning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=9GKURFWGeh},
}

@inproceedings{neurips2025_transformers_76776,
  title = {{Transformers for Mixed-type Event Sequences}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=MtwsRjPZhf},
}

@inproceedings{neurips2026_one_94663,
  title = {{One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150016},
}

@inproceedings{aaai2026_seqret_106296,
  title = {{SEQRET: Mining Rule Sets from Event Sequences}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38603},
}

@inproceedings{aaai2024_a_4999,
  title = {{A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30190},
}

@inproceedings{icml2024_probabilistic_43455,
  title = {{Probabilistic Modeling of Interpersonal Coordination Processes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34997},
}

@inproceedings{icml2025_conformal_46531,
  title = {{Conformal Anomaly Detection in Event Sequences}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46037},
}

@inproceedings{icml2025_revisiting_47235,
  title = {{Revisiting the Predictability of Performative, Social Events}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45352},
}

@inproceedings{icml2025_evolving_47248,
  title = {{Evolving Minds: Logic-Informed Inference from Temporal Action Patterns}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45341},
}

@inproceedings{icml2026_time_51073,
  title = {{Time-Conditioned Foreseeing: An EHR-Specific Foundation Model for Irregular Dynamics and Calendrical Time}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=IalpB5Mzaz},
}

@inproceedings{neurips2026_realism_94917,
  title = {{Realism VS Accuracy: Event Sequence Forecasting from a Generative Modeling Perspective}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/139504},
}