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

@inproceedings{neurips2017_neural_56507,
  title = {{Neural Discrete Representation Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9401},
}

@inproceedings{icml2018_a_36473,
  title = {{A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2420},
}

@inproceedings{aaai2019_infovae_101823,
  title = {{InfoVAE: Balancing Learning and Inference in Variational Autoencoders}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4538},
}

@inproceedings{icml2016_auxiliary_35748,
  title = {{Auxiliary Deep Generative Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/maaloe16.html},
}

@inproceedings{neurips2016_ladder_55804,
  title = {{Ladder Variational Autoencoders}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7353},
}

@inproceedings{iclr2017_variational_28246,
  title = {{Variational Lossy Autoencoder}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=BysvGP5ee},
}

@inproceedings{neurips2017_unsupervised_56752,
  title = {{Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8977},
}

@inproceedings{aaai2018_multi_105758,
  title = {{Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11867},
}

@inproceedings{neurips2018_isolating_57253,
  title = {{Isolating Sources of Disentanglement in Variational Autoencoders}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11269},
}

@inproceedings{icml2021_conditional_39156,
  title = {{Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9245},
}

@inproceedings{neurips2018_information_57241,
  title = {{Information Constraints on Auto-Encoding Variational Bayes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11593},
}

@inproceedings{aaai2018_improving_105900,
  title = {{Improving Variational Encoder-Decoders in Dialogue Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11960},
}

@inproceedings{icml2018_inference_36756,
  title = {{Inference Suboptimality in Variational Autoencoders}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2425},
}

@inproceedings{iclr2017_pixelvae_28218,
  title = {{PixelVAE: A Latent Variable Model for Natural Images}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=BJKYvt5lg},
}

@inproceedings{iclr2019_sliced_28887,
  title = {{Sliced Wasserstein Auto-Encoders}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/1081},
}

@inproceedings{aaai2018_variational_105925,
  title = {{Variational Recurrent Neural Machine Translation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11985},
}

@inproceedings{cvpr2017_factorized_12260,
  title = {{Factorized Variational Autoencoders for Modeling Audience Reactions to Movies}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{iclr2019_variational_29109,
  title = {{Variational Autoencoder with Arbitrary Conditioning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/659},
}

@inproceedings{iclr2019_understanding_29008,
  title = {{Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/799},
}

@inproceedings{aaai2017_salience_105978,
  title = {{Salience Estimation via Variational Auto-Encoders for Multi-Document Summarization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11007},
}

@inproceedings{neurips2024_unity_72735,
  title = {{Unity by Diversity: Improved Representation Learning for Multimodal VAEs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94655},
}

@inproceedings{icml2025_latent_49037,
  title = {{Latent Thought Models with Variational Bayes Inference-Time Computation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43587},
}

@inproceedings{aaai2025_cssinger_8366,
  title = {{CSSinger: End-to-End Chunkwise Streaming Singing Voice Synthesis System Based on Conditional Variational Autoencoder}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34541},
}

@inproceedings{iclr2024_t_34451,
  title = {{\$t^3\$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18623},
}

@inproceedings{icml2026_training_49398,
  title = {{Training-Free Vector Quantization via Gaussian VAEs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=2CQkqiZ6p9},
}

@inproceedings{icml2026_sparse_53554,
  title = {{Sparse Autoencoders are Topic Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=gXXrubolmR},
}

@inproceedings{neurips2025_inverse_75600,
  title = {{Inverse Optimization Latent Variable Models for Learning Costs Applied to Route Problems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=9vDpL9lgKS},
}

@inproceedings{neurips2025_latent_75772,
  title = {{Latent Space Factorization in LoRA}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Bqui2s3xFi},
}

@inproceedings{neurips2025_information_77034,
  title = {{Information-theoretic Generalization Analysis for VQ-VAEs: A Role of Latent Variables}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=PllZG6K37g},
}

@inproceedings{iclr2025_continuous_82776,
  title = {{Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29023},
}

@inproceedings{iclr2026_bi_88853,
  title = {{Bi-Lipschitz Autoencoder With Injectivity Guarantee}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=rl2dPJEk8b},
}

@inproceedings{iclr2026_synthesising_89503,
  title = {{Synthesising Counterfactual Explanations via Label-Conditional Gaussian Mixture Variational Autoencoders}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=zd9R2T4HiX},
}

@inproceedings{neurips2026_toward_90725,
  title = {{Toward the Goldilocks Blind Compression of Quantum States}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151181},
}

@inproceedings{neurips2026_casl_95198,
  title = {{CASL-VAE: Learning Structured Latent Variables from Unpaired Data for Semi-supervised Clustering and Paired Sample Generation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150313},
}

@inproceedings{cvpr2026_veni_97127,
  title = {{VENI: Variational Encoder for Natural Illumination}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Walker_VENI_Variational_Encoder_for_Natural_Illumination_CVPR_2026_paper.html},
}

@inproceedings{aaai2026_multimodal_100455,
  title = {{Multimodal Gaussian Mixture Variational Autoencoder with Consistency Regularizations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37302},
}

@inproceedings{iclr2024_compressing_35039,
  title = {{Compressing Latent Space via Least Volume}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18035},
}

@inproceedings{icml2026_information_50085,
  title = {{Information-Theoretic Generalization Bounds for VAEs: A Role of Encoder and Latent Variable}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=8vqmDcqeg6},
}

@inproceedings{icml2026_h_51364,
  title = {{Hölder++: Improving Quality-Coherence Trade-off in Multimodal VAEs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=LQ3TocqrTh},
}

@inproceedings{iclr2025_high_82176,
  title = {{High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29615},
}