% Key papers for Hierarchical VAEs and posterior collapse (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2019_biva_57929,
  title = {{BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13765},
}

@inproceedings{icml2017_grammar_36212,
  title = {{Grammar Variational Autoencoder}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/859},
}

@inproceedings{aaai2022_factorvae_2083,
  title = {{FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/04468-factorvae-a-probabilistic-dynamic-factor-model-based-on-variational-autoencoder-for-predicting-cross-sectional-stock-returns/},
}

@inproceedings{neurips2020_likelihood_60250,
  title = {{Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16848},
}

@inproceedings{iclr2019_practical_29199,
  title = {{Practical lossless compression with latent variables using bits back coding}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/689},
}

@inproceedings{cvpr2019_disentangling_14091,
  title = {{Disentangling Latent Space for VAE by Label Relevant/Irrelevant Dimensions}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2022_unified_20126,
  title = {{Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{iclr2019_integer_29030,
  title = {{Integer Networks for Data Compression with Latent-Variable Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/1017},
}

@inproceedings{aaai2019_unsupervised_101699,
  title = {{Unsupervised Learning with Contrastive Latent Variable Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4414},
}

@inproceedings{icml2020_the_38857,
  title = {{The Usual Suspects? Reassessing Blame for VAE Posterior Collapse}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6433},
}

@inproceedings{iclr2018_latent_28610,
  title = {{Latent Space Oddity: on the Curvature of Deep Generative Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/130},
}

@inproceedings{neurips2019_copulas_58053,
  title = {{Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13763},
}

@inproceedings{cvpr2025_robust_27483,
  title = {{Robust Multimodal Survival Prediction with Conditional Latent Differentiation Variational AutoEncoder}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34326},
}

@inproceedings{aaai2019_understanding_101827,
  title = {{Understanding VAEs in Fisher-Shannon Plane}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4542},
}

@inproceedings{cvpr2022_robust_19758,
  title = {{Robust Outlier Detection by De-Biasing VAE Likelihoods}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2024_learned_23940,
  title = {{Learned Lossless Image Compression based on Bit Plane Slicing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30707},
}

@inproceedings{iclr2019_preventing_28759,
  title = {{Preventing Posterior Collapse with delta-VAEs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/1047},
}

@inproceedings{neurips2019_exact_58230,
  title = {{Exact Rate-Distortion in Autoencoders via Echo Noise}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13551},
}

@inproceedings{iclr2021_property_30693,
  title = {{Property Controllable Variational Autoencoder via Invertible Mutual Dependence}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2938},
}

@inproceedings{icml2021_hierarchical_39420,
  title = {{Hierarchical VAEs Know What They Don’t Know}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9665},
}

@inproceedings{aaai2024_distribution_5723,
  title = {{Distribution-Conditioned Adversarial Variational Autoencoder for Valid Instrumental Variable Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29271},
}

@inproceedings{icml2025_mitigating_45873,
  title = {{MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46670},
}

@inproceedings{neurips2024_metric_73325,
  title = {{Metric Space Magnitude for Evaluating the Diversity of Latent Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94120},
}

@inproceedings{icml2024_preventing_43439,
  title = {{Preventing Model Collapse in Gaussian Process Latent Variable Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35013},
}

@inproceedings{icml2024_latent_45009,
  title = {{Latent variable model for high-dimensional point process with structured missingness}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33443},
}

@inproceedings{icml2025_enforcing_46586,
  title = {{Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45983},
}

@inproceedings{icml2025_sparse_49024,
  title = {{Sparse Autoencoders, Again?}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43600},
}

@inproceedings{icml2026_geodesic_49742,
  title = {{Geodesic Calculus on Implicitly Defined Latent Manifolds}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=5LBH6azyBM},
}

@inproceedings{neurips2025_dimensional_80022,
  title = {{Dimensional Collapse in VQVAEs: Evidence and Remedies}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=vJtnJfS2mQ},
}

@inproceedings{iclr2025_towards_81445,
  title = {{Towards Scalable Topological Regularizers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30329},
}

@inproceedings{iclr2025_isometric_84025,
  title = {{Isometric Regularization for Manifolds of Functional Data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27800},
}

@inproceedings{iclr2026_quasi_87803,
  title = {{Quasi-Monte Carlo Methods Enable Extremely Low-Dimensional Deep Generative Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=fdLU72nQdr},
}

@inproceedings{iclr2026_latent_89033,
  title = {{Latent Stochastic Interpolants}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=txiGUfI4yF},
}

@inproceedings{neurips2026_amortized_93124,
  title = {{Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152433},
}

@inproceedings{neurips2026_environment_94689,
  title = {{Environment-Robust Representation Learning with Empirical Bayes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151010},
}

@inproceedings{iclr2025_bayesian_82378,
  title = {{Bayesian Regularization of Latent Representation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29414},
}

@inproceedings{iclr2026_gensr_84954,
  title = {{GenSR: Symbolic regression based on equation generative space}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=8emIjwUQZg},
}

@inproceedings{iclr2026_navigating_87279,
  title = {{Navigating the Latent Space Dynamics of Neural Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=Zunww3FHPU},
}