% Key papers for Normalizing flow training and design (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2016_improved_55785,
  title = {{Improved Variational Inference with Inverse Autoregressive Flow}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6943},
}

@inproceedings{icml2020_normalizing_38519,
  title = {{Normalizing Flows on Tori and Spheres}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6493},
}

@inproceedings{icml2020_equivariant_38165,
  title = {{Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6834},
}

@inproceedings{neurips2019_discrete_58144,
  title = {{Discrete Flows: Invertible Generative Models of Discrete Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14383},
}

@inproceedings{aaai2021_ot_1077,
  title = {{OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09223-ot-flow-fast-and-accurate-continuous-normalizing-flows-via-optimal-transport/},
}

@inproceedings{icml2019_latent_37469,
  title = {{Latent Normalizing Flows for Discrete Sequences}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4292},
}

@inproceedings{neurips2020_stochastic_60879,
  title = {{Stochastic Normalizing Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18584},
}

@inproceedings{neurips2020_survae_60905,
  title = {{SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18708},
}

@inproceedings{icml2020_semi_38748,
  title = {{Semi-Supervised Learning with Normalizing Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6343},
}

@inproceedings{neurips2020_riemannian_60726,
  title = {{Riemannian Continuous Normalizing Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17432},
}

@inproceedings{neurips2020_why_61106,
  title = {{Why Normalizing Flows Fail to Detect Out-of-Distribution Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18088},
}

@inproceedings{icml2018_continuous_36598,
  title = {{Continuous-Time Flows for Efficient Inference and Density Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2258},
}

@inproceedings{neurips2019_neural_58671,
  title = {{Neural Spline Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13834},
}

@inproceedings{iclr2023_building_33107,
  title = {{Building Normalizing Flows with Stochastic Interpolants}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/10866},
}

@inproceedings{neurips2020_wavelet_61087,
  title = {{Wavelet Flow: Fast Training of High Resolution Normalizing Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17275},
}

@inproceedings{neurips2021_smooth_63591,
  title = {{Smooth Normalizing Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27193},
}

@inproceedings{neurips2019_invertible_58434,
  title = {{Invertible Convolutional Flow}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14535},
}

@inproceedings{iclr2023_flow_32721,
  title = {{Flow Annealed Importance Sampling Bootstrap}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11801},
}

@inproceedings{iclr2021_categorical_29923,
  title = {{Categorical Normalizing Flows via Continuous Transformations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2730},
}

@inproceedings{neurips2021_densely_61886,
  title = {{Densely connected normalizing flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28026},
}

@inproceedings{aaai2024_robustly_7183,
  title = {{Robustly Train Normalizing Flows via KL Divergence Regularization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29426},
}

@inproceedings{icml2024_on_45613,
  title = {{On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32839},
}

@inproceedings{neurips2024_mutual_71565,
  title = {{Mutual Information Estimation via Normalizing Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95704},
}

@inproceedings{cvpr2024_normalizing_24300,
  title = {{Normalizing Flows on the Product Space of SO(3) Manifolds for Probabilistic Human Pose Modeling}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30757},
}

@inproceedings{iclr2024_lifting_35084,
  title = {{Lifting Architectural Constraints of Injective Flows}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17989},
}

@inproceedings{iclr2024_fast_35701,
  title = {{Fast and unified path gradient estimators for normalizing flows}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17372},
}

@inproceedings{neurips2024_preferential_74153,
  title = {{Preferential Normalizing Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93389},
}

@inproceedings{neurips2025_path_77669,
  title = {{Path Gradients after Flow Matching}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=WFujqJ5UBV},
}

@inproceedings{iclr2024_kernelised_35010,
  title = {{Kernelised Normalising Flows}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18064},
}

@inproceedings{icml2024_conditional_44238,
  title = {{Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34214},
}

@inproceedings{icml2024_reflected_44454,
  title = {{Reflected Flow Matching}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33998},
}

@inproceedings{icml2025_flexible_47722,
  title = {{Flexible Tails for Normalizing Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44878},
}

@inproceedings{icml2025_annealing_48255,
  title = {{Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44357},
}

@inproceedings{icml2025_importance_49089,
  title = {{Importance Corrected Neural JKO Sampling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43535},
}

@inproceedings{neurips2025_multivariate_79245,
  title = {{Multivariate Latent Recalibration for Conditional Normalizing Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=nO8ShqG2ci},
}

@inproceedings{iclr2025_injective_81697,
  title = {{Injective flows for star-like manifolds}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30082},
}

@inproceedings{cvpr2026_bidirectional_98798,
  title = {{Bidirectional Normalizing Flow: From Data to Noise and Back}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Lu_Bidirectional_Normalizing_Flow_From_Data_to_Noise_and_Back_CVPR_2026_paper.html},
}

@inproceedings{aaai2026_flowing_100453,
  title = {{Flowing Backwards: Improving Normalizing Flows via Reverse Representation Alignment}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37300},
}

@inproceedings{iclr2026_structured_85982,
  title = {{Structured Flow Autoencoders: Learning Structured Probabilistic Representations with Flow Matching}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=KYdfvF2SZN},
}

@inproceedings{neurips2026_symplectic_91181,
  title = {{Symplectic Normal Coordinates Flow for Generative Modeling of Hamiltonian Systems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/155724},
}