% Key papers for Flow-based density estimation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_masked_56464,
  title = {{Masked Autoregressive Flow for Density Estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9021},
}

@inproceedings{iclr2019_do_28890,
  title = {{Do Deep Generative Models Know What They Don't Know?}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/1015},
}

@inproceedings{icml2019_sum_37776,
  title = {{Sum-of-Squares Polynomial Flow}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3638},
}

@inproceedings{icml2019_autoregressive_37171,
  title = {{Autoregressive Energy Machines}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3871},
}

@inproceedings{icml2018_deep_36620,
  title = {{Deep Density Destructors}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2437},
}

@inproceedings{cvpr2022_efficient_18739,
  title = {{Efficient Maximal Coding Rate Reduction by Variational Forms}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{neurips2020_log_60266,
  title = {{Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17922},
}

@inproceedings{icml2024_an_45614,
  title = {{An amortized approach to non-linear mixed-effects modeling based on neural posterior estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32838},
}

@inproceedings{aaai2024_understanding_7684,
  title = {{Understanding Likelihood of Normalizing Flow and Image Complexity through the Lens of Out-of-Distribution Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30146},
}

@inproceedings{neurips2020_improved_60059,
  title = {{Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16843},
}

@inproceedings{neurips2020_relative_60698,
  title = {{Relative gradient optimization of the Jacobian term in unsupervised deep learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17805},
}

@inproceedings{neurips2022_normalizing_65636,
  title = {{Normalizing Flows for Knockoff-free Controlled Feature Selection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52885},
}

@inproceedings{aaai2023_positive_4390,
  title = {{Positive Distribution Pollution: Rethinking Positive Unlabeled Learning from a Unified Perspective}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26051},
}

@inproceedings{neurips2020_invertible_60110,
  title = {{Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18714},
}

@inproceedings{aaai2023_a_3012,
  title = {{A Probabilistic Graph Diffusion Model for Source Localization (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27013},
}

@inproceedings{aaai2025_enhanced_8946,
  title = {{Enhanced Importance Sampling Through Latent Space Exploration in Normalizing Flows}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33978},
}

@inproceedings{iclr2022_group_31777,
  title = {{Group equivariant neural posterior estimation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6752},
}

@inproceedings{aaai2023_efficient_3555,
  title = {{Efficient Non-parametric Neural Density Estimation and Its Application to Outlier and Anomaly Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26919},
}

@inproceedings{iclr2022_adavi_31012,
  title = {{ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6309},
}

@inproceedings{icml2024_learning_43678,
  title = {{Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34774},
}

@inproceedings{icml2024_a_43870,
  title = {{A Geometric Explanation of the Likelihood OOD Detection Paradox}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34582},
}

@inproceedings{icml2025_learning_47367,
  title = {{Learning Distances from Data with Normalizing Flows and Score Matching}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45225},
}

@inproceedings{icml2026_flow_49817,
  title = {{Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=5zbPdMNcl9},
}

@inproceedings{neurips2024_optimal_70341,
  title = {{Optimal Classification under Performative Distribution Shift}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96756},
}

@inproceedings{neurips2025_partial_77728,
  title = {{Partial Information Decomposition via Normalizing Flows in Latent Gaussian Distributions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=X13jOIhnog},
}

@inproceedings{icml2026_noise_52026,
  title = {{Noise-Robust Density Estimation for Tabular Data Anomaly Detection}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=S51EtVGlui},
}