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

@inproceedings{aaai2016_drimux_104804,
  title = {{DRIMUX: Dynamic Rumor Influence Minimization with User Experience in Social Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10063},
}

@inproceedings{aaai2021_fair_590,
  title = {{Fair Influence Maximization: a Welfare Optimization Approach}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/11630-fair-influence-maximization-a-welfare-optimization-approach/},
}

@inproceedings{neurips2017_balancing_56170,
  title = {{Balancing information exposure in social networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9243},
}

@inproceedings{aaai2019_coverage_99937,
  title = {{Coverage Centrality Maximization in Undirected Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3823},
}

@inproceedings{aaai2016_fast_104799,
  title = {{Fast Optimal Clearing of Capped-Chain Barter Exchanges}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10053},
}

@inproceedings{aaai2020_balancing_99726,
  title = {{Balancing Spreads of Influence in a Social Network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5327},
}

@inproceedings{neurips2019_adaptive_57871,
  title = {{Adaptive Influence Maximization with Myopic Feedback}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13685},
}

@inproceedings{neurips2021_minimizing_63576,
  title = {{Minimizing Polarization and Disagreement in Social Networks via Link Recommendation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28694},
}

@inproceedings{neurips2016_maximizing_55866,
  title = {{Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/8514},
}

@inproceedings{neurips2017_the_56717,
  title = {{The Importance of Communities for Learning to Influence}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9359},
}

@inproceedings{neurips2020_decisions_59646,
  title = {{Decisions, Counterfactual Explanations and Strategic Behavior}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17146},
}

@inproceedings{aaai2020_adaptive_100225,
  title = {{Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5398},
}

@inproceedings{aaai2022_fixation_2116,
  title = {{Fixation Maximization in the Positional Moran Process}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/09304-fixation-maximization-in-the-positional-moran-process/},
}

@inproceedings{neurips2016_computing_55638,
  title = {{Computing and maximizing influence in linear threshold and triggering models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6954},
}

@inproceedings{icml2019_robust_37705,
  title = {{Robust Influence Maximization for Hyperparametric Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3771},
}

@inproceedings{aaai2020_gradient_99731,
  title = {{Gradient Method for Continuous Influence Maximization with Budget-Saving Considerations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5332},
}

@inproceedings{aaai2025_a_7933,
  title = {{A Thorough Comparison Between Independent Cascade and Susceptible-Infected-Recovered Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32028},
}

@inproceedings{aaai2018_maximizing_100586,
  title = {{Maximizing Activity in Ising Networks via the TAP Approximation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11333},
}

@inproceedings{aaai2023_diversity_3487,
  title = {{Diversity Maximization in the Presence of Outliers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26454},
}

@inproceedings{aaai2018_scalable_106145,
  title = {{Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11340},
}

@inproceedings{aaai2025_hyperparametric_9481,
  title = {{Hyperparametric Robust and Dynamic Influence Maximization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33362},
}

@inproceedings{neurips2024_motif_74290,
  title = {{Motif-oriented influence maximization for viral marketing in large-scale social networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93268},
}

@inproceedings{aaai2026_city_106437,
  title = {{City Sampling for Citizens’ Assemblies}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38744},
}

@inproceedings{icml2026_eigencache_50378,
  title = {{EigenCache: Rethinking Diffusion Acceleration as Covariance-Optimal Forecasting and Submodular Information Allocation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=BjMsVqss9N},
}