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

@inproceedings{icml2019_flow_37380,
  title = {{Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3759},
}

@inproceedings{neurips2018_glow_57180,
  title = {{Glow: Generative Flow with Invertible 1x1 Convolutions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11968},
}

@inproceedings{icml2019_invertible_37456,
  title = {{Invertible Residual Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4295},
}

@inproceedings{neurips2019_residual_58907,
  title = {{Residual Flows for Invertible Generative Modeling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14581},
}

@inproceedings{iclr2019_ffjord_29169,
  title = {{FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/778},
}

@inproceedings{cvpr2021_ivpf_18170,
  title = {{iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{neurips2019_compression_58019,
  title = {{Compression with Flows via Local Bits-Back Coding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14519},
}

@inproceedings{iclr2021_idf_30215,
  title = {{IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2779},
}

@inproceedings{icml2019_hybrid_37430,
  title = {{Hybrid Models with Deep and Invertible Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4312},
}

@inproceedings{icml2020_approximation_37946,
  title = {{Approximation Capabilities of Neural ODEs and Invertible Residual Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5911},
}

@inproceedings{neurips2022_manifold_65397,
  title = {{Manifold Interpolating Optimal-Transport Flows for Trajectory Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54538},
}

@inproceedings{icml2020_tails_38828,
  title = {{Tails of Lipschitz Triangular Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6006},
}

@inproceedings{neurips2020_hypersolvers_60033,
  title = {{Hypersolvers: Toward Fast Continuous-Depth Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18757},
}

@inproceedings{aaai2021_hint_697,
  title = {{HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08191-hint-hierarchical-invertible-neural-transport-for-density-estimation-and-bayesian-inference/},
}

@inproceedings{icml2020_relaxing_38690,
  title = {{Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6505},
}

@inproceedings{icml2020_vflow_38915,
  title = {{VFlow: More Expressive Generative Flows with Variational Data Augmentation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6019},
}

@inproceedings{neurips2020_greedy_59974,
  title = {{Greedy inference with structure-exploiting lazy maps}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18937},
}

@inproceedings{neurips2019_integer_58421,
  title = {{Integer Discrete Flows and Lossless Compression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14180},
}

@inproceedings{neurips2019_unconstrained_59132,
  title = {{Unconstrained Monotonic Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13369},
}

@inproceedings{neurips2021_iflow_62335,
  title = {{iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Coder}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27304},
}

@inproceedings{iclr2024_flow_34917,
  title = {{Flow Matching on General Geometries}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18157},
}

@inproceedings{icml2025_scalable_47456,
  title = {{Scalable Equilibrium Sampling with Sequential Boltzmann Generators}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45137},
}

@inproceedings{iclr2025_designing_82373,
  title = {{Designing Mechanical Meta-Materials by Learning Equivariant Flows}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29419},
}

@inproceedings{aaai2025_a_7931,
  title = {{A Theoretical Framework for an Efficient Normalizing Flow-Based Solution to the Electronic Schrödinger Equation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/31996},
}

@inproceedings{aaai2025_flow_9210,
  title = {{Flow Factorization for Efficient Generative Flow Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34887},
}

@inproceedings{icml2025_score_46385,
  title = {{Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46179},
}

@inproceedings{icml2025_ergodic_46732,
  title = {{Ergodic Generative Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45840},
}

@inproceedings{icml2025_computing_47575,
  title = {{Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45021},
}

@inproceedings{icml2026_autoregressive_49906,
  title = {{Autoregressive Boltzmann Generators}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=75AYDsndHP},
}

@inproceedings{icml2026_analytic_50175,
  title = {{Analytic Bijections for Smooth and Interpretable Normalizing Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=9kkrASoSbp},
}

@inproceedings{icml2026_unfolding_55369,
  title = {{Unfolding Generative Flows with Koopman Operators: Trajectory-Preserving Linearization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=yKgAjMNkQO},
}

@inproceedings{neurips2025_asymptotically_76783,
  title = {{Asymptotically exact variational flows via involutive MCMC kernels}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=MykdD1wZDV},
}

@inproceedings{iclr2025_towards_80866,
  title = {{Towards Hierarchical Rectified Flow}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30901},
}

@inproceedings{iclr2026_falcon_85531,
  title = {{FALCON: Few-step Accurate Likelihoods for Continuous Flows}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=FbssShlI4N},
}

@inproceedings{iclr2026_flow_85631,
  title = {{Flow Straight and Fast in Hilbert Space: Functional Rectified Flow}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=GWK8fm1r9y},
}

@inproceedings{iclr2026_efficient_87560,
  title = {{Efficient Regression-based Training of Normalizing Flows for Boltzmann Generators}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=ctdnzPxDI3},
}

@inproceedings{neurips2026_fmmi_92997,
  title = {{FMMI: Flow Matching Mutual Information Estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/148155},
}

@inproceedings{neurips2026_few_93345,
  title = {{Few-Step Boltzmann Generators via Scalable Likelihood Flow Maps}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/154720},
}

@inproceedings{neurips2026_structured_94993,
  title = {{Structured Coupling for Flow Matching}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153603},
}

@inproceedings{neurips2025_amortized_76577,
  title = {{Amortized Variational Transdimensional Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=KqhMpsWiz2},
}