% Key papers for Proximal and deep causal effect estimation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2016_recommendations_35961,
  title = {{Recommendations as Treatments: Debiasing Learning and Evaluation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/schnabel16.html},
}

@inproceedings{neurips2020_estimating_59801,
  title = {{Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16932},
}

@inproceedings{neurips2020_identifying_60039,
  title = {{Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18150},
}

@inproceedings{aaai2018_generalized_103378,
  title = {{Generalized Adjustment Under Confounding and Selection Biases}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/12125},
}

@inproceedings{icml2019_validating_37843,
  title = {{Validating Causal Inference Models via Influence Functions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3882},
}

@inproceedings{aaai2020_a_103176,
  title = {{A Causal Inference Method for Reducing Gender Bias in Word Embedding Relations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6486},
}

@inproceedings{neurips2019_using_59166,
  title = {{Using Embeddings to Correct for Unobserved Confounding in Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14310},
}

@inproceedings{aaai2023_direct_3471,
  title = {{Direct Heterogeneous Causal Learning for Resource Allocation Problems in Marketing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25677},
}

@inproceedings{icml2022_causal_40322,
  title = {{Causal Transformer for Estimating Counterfactual Outcomes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17693},
}

@inproceedings{iclr2021_vcnet_30316,
  title = {{VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2904},
}

@inproceedings{aaai2022_heterogeneous_2189,
  title = {{Heterogeneous Peer Effects in the Linear Threshold Model}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/04175-heterogeneous-peer-effects-in-the-linear-threshold-model/},
}

@inproceedings{neurips2020_reconsidering_60675,
  title = {{Reconsidering Generative Objectives For Counterfactual Reasoning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18112},
}

@inproceedings{aaai2023_weather2vec_4961,
  title = {{Weather2vec: Representation Learning for Causal Inference with Non-local Confounding in Air Pollution and Climate Studies}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26696},
}

@inproceedings{aaai2024_causal_5384,
  title = {{Causal Walk: Debiasing Multi-Hop Fact Verification with Front-Door Adjustment}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29925},
}

@inproceedings{neurips2019_covariate_58064,
  title = {{Covariate-Powered Empirical Bayes Estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13996},
}

@inproceedings{icml2021_proximal_39832,
  title = {{Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9925},
}

@inproceedings{neurips2022_using_64285,
  title = {{Using Embeddings for Causal Estimation of Peer Influence in Social Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53781},
}

@inproceedings{aaai2022_bounds_1799,
  title = {{Bounds on Causal Effects and Application to High Dimensional Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/05773-bounds-on-causal-effects-and-application-to-high-dimensional-data/},
}

@inproceedings{neurips2021_causal_61194,
  title = {{Causal Effect Inference for Structured Treatments}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26383},
}

@inproceedings{iclr2024_debiased_34020,
  title = {{Debiased Collaborative Filtering with Kernel-Based Causal Balancing}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19055},
}

@inproceedings{aaai2024_nester_6735,
  title = {{NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29398},
}

@inproceedings{icml2024_hybrid_43946,
  title = {{Hybrid\$^2\$ Neural ODE Causal Modeling and an Application to Glycemic Response}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34506},
}

@inproceedings{iclr2024_a_35022,
  title = {{A Neural Framework for Generalized Causal Sensitivity Analysis}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18052},
}

@inproceedings{neurips2024_causal_72917,
  title = {{Causal Contrastive Learning for Counterfactual Regression Over Time}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94494},
}

@inproceedings{neurips2024_diffpo_73760,
  title = {{DiffPO: A causal diffusion model for learning distributions of potential outcomes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93743},
}

@inproceedings{aaai2026_invariant_106211,
  title = {{Invariant Feature Learning for Counterfactual Watch-time Prediction in Video Recommendation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38518},
}

@inproceedings{aaai2025_alleviating_8090,
  title = {{Alleviating Dual Biases in Recommendation (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35273},
}

@inproceedings{aaai2025_mediation_9929,
  title = {{Mediation Analysis for Probabilities of Causation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34886},
}

@inproceedings{aaai2025_pcm_10237,
  title = {{PCM Selector: Penalized Covariate-Mediator Selection Operator for Evaluating Linear Causal Effects}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34889},
}

@inproceedings{iclr2024_be_33634,
  title = {{Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19441},
}

@inproceedings{iclr2024_doubly_34517,
  title = {{Doubly Robust Proximal Causal Learning for Continuous Treatments}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18557},
}

@inproceedings{icml2024_doubly_43487,
  title = {{Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34965},
}

@inproceedings{icml2024_causal_43992,
  title = {{Causal Inference from Competing Treatments}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34460},
}

@inproceedings{icml2024_collaborative_44151,
  title = {{Collaborative Heterogeneous Causal Inference Beyond Meta-analysis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34301},
}

@inproceedings{icml2025_generalized_45933,
  title = {{Generalized Random Forests Using Fixed-Point Trees}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46613},
}

@inproceedings{icml2025_causal_45997,
  title = {{Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46549},
}

@inproceedings{icml2025_transformer_47689,
  title = {{Transformer-Based Spatial-Temporal Counterfactual Outcomes Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44908},
}

@inproceedings{icml2026_causal_51117,
  title = {{Causal Matrix Completion under Multiple Treatments via Mixed Synthetic Nearest Neighbors}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Ir6N7U5Kea},
}