% Key papers for Amortized and online variational inference (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2016_neural_35915,
  title = {{Neural Variational Inference for Text Processing}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/miao16.html},
}

@inproceedings{neurips2019_variational_59179,
  title = {{Variational Denoising Network: Toward Blind Noise Modeling and Removal}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13378},
}

@inproceedings{iclr2017_autoencoding_28236,
  title = {{Autoencoding Variational Inference For Topic Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=BybtVK9lg},
}

@inproceedings{icml2019_on_37598,
  title = {{On Variational Bounds of Mutual Information}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4330},
}

@inproceedings{iclr2020_empirical_29497,
  title = {{Empirical Bayes Transductive Meta-Learning with Synthetic Gradients}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=Hkg-xgrYvH},
}

@inproceedings{iclr2017_deep_28288,
  title = {{Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=HyTqHL5xg},
}

@inproceedings{icml2018_iterative_36763,
  title = {{Iterative Amortized Inference}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2110},
}

@inproceedings{aaai2020_variational_101276,
  title = {{Variational Pathway Reasoning for EEG Emotion Recognition}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5657},
}

@inproceedings{icml2019_variational_37846,
  title = {{Variational Inference for sparse network reconstruction from count data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3682},
}

@inproceedings{icml2018_tighter_37049,
  title = {{Tighter Variational Bounds are Not Necessarily Better}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2399},
}

@inproceedings{iclr2018_variational_28557,
  title = {{Variational Message Passing with Structured Inference Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/136},
}

@inproceedings{neurips2018_coupled_56986,
  title = {{Coupled Variational Bayes via Optimization Embedding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11921},
}

@inproceedings{neurips2019_variational_59183,
  title = {{Variational Temporal Abstraction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14139},
}

@inproceedings{icml2019_an_37152,
  title = {{An Instability in Variational Inference for Topic Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3966},
}

@inproceedings{neurips2020_learning_60228,
  title = {{Learning to Learn Variational Semantic Memory}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16927},
}

@inproceedings{icml2019_variational_37845,
  title = {{Variational Implicit Processes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4123},
}

@inproceedings{icml2020_learning_38389,
  title = {{Learning Robot Skills with Temporal Variational Inference}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6238},
}

@inproceedings{icml2020_learning_38407,
  title = {{Learning to Learn Kernels with Variational Random Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6847},
}

@inproceedings{neurips2018_a_56797,
  title = {{A General Method for Amortizing Variational Filtering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11754},
}

@inproceedings{aaai2018_variational_106147,
  title = {{Variational BOLT: Approximate Learning in Factorial Hidden Markov Models With Application to Energy Disaggregation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11342},
}

@inproceedings{icml2025_synonymous_48263,
  title = {{Synonymous Variational Inference for Perceptual Image Compression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44349},
}

@inproceedings{neurips2024_sharpness_72039,
  title = {{Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95279},
}

@inproceedings{icml2026_variational_49990,
  title = {{Variational Speculative Decoding: Rethinking Draft Training from Token Likelihood to Sequence Acceptance}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=7xO0ADKJu8},
}

@inproceedings{icml2026_mavrl_51228,
  title = {{MAVRL: Learning Reward Functions from Multiple Feedback Types with Amortized Variational Inference}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=K0ypMhiYe0},
}

@inproceedings{neurips2025_brain_75175,
  title = {{Brain-like Variational Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=573IcLusXq},
}

@inproceedings{iclr2025_variational_80591,
  title = {{Variational Search Distributions}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31174},
}

@inproceedings{neurips2026_annealing_91671,
  title = {{Annealing in variational inference mitigates mode collapse: a theoretical study on Gaussian mixtures}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151971},
}

@inproceedings{icml2025_multilayer_46572,
  title = {{Multilayer Matrix Factorization via Dimension-Reducing Diffusion Variational Inference}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45997},
}

@inproceedings{icml2025_variational_48148,
  title = {{Variational Counterfactual Intervention Planning to Achieve Target Outcomes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44461},
}

@inproceedings{icml2026_amortized_51267,
  title = {{Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=KODJBT02ux},
}

@inproceedings{icml2026_spectral_51302,
  title = {{Spectral Bridge Variational Inference: Dynamic LoRA via Bures-Wasserstein Gradient Flows}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=KjF35IhQGS},
}

@inproceedings{iclr2026_variational_87480,
  title = {{Variational Inference for Cyclic Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=c1jWNZ1Zqg},
}

@inproceedings{iclr2026_variational_87768,
  title = {{Variational Reasoning for Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=fGGcovg6oW},
}