% Key papers for Variational methods for sequence models (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2016_composing_55636,
  title = {{Composing graphical models with neural networks for structured representations and fast inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6917},
}

@inproceedings{icml2017_discovering_36157,
  title = {{Discovering Discrete Latent Topics with Neural Variational Inference}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/776},
}

@inproceedings{neurips2016_sequential_55990,
  title = {{Sequential Neural Models with Stochastic Layers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7212},
}

@inproceedings{aaai2020_latent_103103,
  title = {{Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6413},
}

@inproceedings{neurips2018_latent_57268,
  title = {{Latent Alignment and Variational Attention}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11923},
}

@inproceedings{iclr2018_whai_28585,
  title = {{WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/42},
}

@inproceedings{neurips2017_differentiable_56253,
  title = {{Differentiable Learning of Submodular Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8895},
}

@inproceedings{icml2018_fixing_36702,
  title = {{Fixing a Broken ELBO}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2442},
}

@inproceedings{neurips2018_learning_57285,
  title = {{Learning Invariances using the Marginal Likelihood}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11943},
}

@inproceedings{neurips2018_the_57684,
  title = {{The Description Length of Deep Learning models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11232},
}

@inproceedings{neurips2017_z_56779,
  title = {{Z-Forcing: Training Stochastic Recurrent Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9439},
}

@inproceedings{icml2016_collapsed_35763,
  title = {{Collapsed Variational Inference for Sum-Product Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/zhaoa16.html},
}

@inproceedings{neurips2020_a_59285,
  title = {{A Variational Approach for Learning from Positive and Unlabeled Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17736},
}

@inproceedings{iclr2021_not_30702,
  title = {{not-MIWAE: Deep Generative Modelling with Missing not at Random Data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2776},
}

@inproceedings{icml2016_bidirectional_35756,
  title = {{Bidirectional Helmholtz Machines}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/bornschein16.html},
}

@inproceedings{neurips2020_a_59242,
  title = {{A Discrete Variational Recurrent Topic Model without the Reparametrization Trick}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18906},
}

@inproceedings{neurips2017_context_56211,
  title = {{Context Selection for Embedding Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9258},
}

@inproceedings{neurips2017_deep_56235,
  title = {{Deep Dynamic Poisson Factorization Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8957},
}

@inproceedings{neurips2018_semi_57615,
  title = {{Semi-crowdsourced Clustering with Deep Generative Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11325},
}

@inproceedings{neurips2018_deep_57015,
  title = {{Deep State Space Models for Unconditional Word Generation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11597},
}

@inproceedings{neurips2024_training_72991,
  title = {{Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94427},
}

@inproceedings{neurips2025_large_77987,
  title = {{Large Language Bayes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=ZtXT584LrT},
}

@inproceedings{neurips2024_on_71834,
  title = {{On Divergence Measures for Training GFlowNets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95464},
}

@inproceedings{neurips2024_what_72316,
  title = {{What type of inference is planning?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95030},
}

@inproceedings{icml2026_pseudo_53473,
  title = {{Pseudo-Mallows for Efficient Probabilistic Preference Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=fotqwXEglz},
}

@inproceedings{neurips2026_cross_93240,
  title = {{Cross-Fitting for Neural Posterior Estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153646},
}