% Key papers for Annealing and divergence-based variational objectives (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2016_a_11378,
  title = {{A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{icml2018_pathwise_36921,
  title = {{Pathwise Derivatives Beyond the Reparameterization Trick}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2213},
}

@inproceedings{neurips2016_relevant_55961,
  title = {{Relevant sparse codes with variational information bottleneck}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7427},
}

@inproceedings{cvpr2017_a_12021,
  title = {{A Non-Convex Variational Approach to Photometric Stereo Under Inaccurate Lighting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{icml2018_message_36847,
  title = {{Message Passing Stein Variational Gradient Descent}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/1915},
}

@inproceedings{icml2018_a_36481,
  title = {{A Spectral Approach to Gradient Estimation for Implicit Distributions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2490},
}

@inproceedings{cvpr2019_a_13798,
  title = {{A Variational EM Framework With Adaptive Edge Selection for Blind Motion Deblurring}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{neurips2016_the_56037,
  title = {{The Generalized Reparameterization Gradient}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7182},
}

@inproceedings{neurips2022_escaping_65762,
  title = {{Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52939},
}

@inproceedings{neurips2018_wasserstein_57775,
  title = {{Wasserstein Variational Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11256},
}

@inproceedings{aaai2016_a_105437,
  title = {{A Unifying Variational Inference Framework for Hierarchical Graph-Coupled HMM with an Application to Influenza Infection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/9894},
}

@inproceedings{cvpr2019_lifting_14468,
  title = {{Lifting Vectorial Variational Problems: A Natural Formulation Based on Geometric Measure Theory and Discrete Exterior Calculus}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{iclr2019_doubly_28926,
  title = {{Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/755},
}

@inproceedings{neurips2019_scalable_58951,
  title = {{Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13621},
}

@inproceedings{icml2021_differentiable_39234,
  title = {{Differentiable Particle Filtering via Entropy-Regularized Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8557},
}

@inproceedings{neurips2017_identification_56370,
  title = {{Identification of Gaussian Process State Space Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9306},
}

@inproceedings{neurips2018_transfer_57732,
  title = {{Transfer of Value Functions via Variational Methods}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11599},
}

@inproceedings{neurips2019_energy_58215,
  title = {{Energy-Inspired Models: Learning with Sampler-Induced Distributions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13911},
}

@inproceedings{icml2019_variational_37848,
  title = {{Variational Russian Roulette for Deep Bayesian Nonparametrics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4118},
}

@inproceedings{aaai2025_q_10404,
  title = {{Q-MAML: Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33995},
}

@inproceedings{aaai2024_gad_6080,
  title = {{GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Framework}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29472},
}

@inproceedings{aaai2025_debiased_8652,
  title = {{Debiased Active Learning with Variational Gradient Rectifier}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33744},
}

@inproceedings{iclr2024_cauchy_33731,
  title = {{Cauchy-Schwarz Divergence Information Bottleneck for Regression}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19344},
}

@inproceedings{iclr2024_variational_35396,
  title = {{Variational Inference for SDEs Driven by Fractional Noise}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17677},
}

@inproceedings{neurips2024_general_72220,
  title = {{General bounds on the quality of Bayesian coresets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95122},
}

@inproceedings{aaai2025_learning_9748,
  title = {{Learning Set Functions with Implicit Differentiation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34178},
}

@inproceedings{icml2024_a_43338,
  title = {{A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35114},
}

@inproceedings{icml2026_variational_51058,
  title = {{Variational inference via Gaussian interacting particles in the Bures-Wasserstein geometry}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=IQojX8HugF},
}

@inproceedings{icml2026_amortized_54714,
  title = {{Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=ronJusfDvK},
}

@inproceedings{icml2026_f_54750,
  title = {{\$f\$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=sDfu0qN6Y6},
}

@inproceedings{neurips2024_asymptotics_71443,
  title = {{Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95813},
}

@inproceedings{neurips2025_rao_76599,
  title = {{Rao-Blackwellised Reparameterisation Gradients}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=L26J2etiCX},
}

@inproceedings{iclr2025_stochastic_83107,
  title = {{Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28700},
}

@inproceedings{neurips2026_tube_94828,
  title = {{TUBE: Tangent Upper Bound on Evidence for Discrete Diffusion Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/155978},
}

@inproceedings{icml2024_differentiable_45517,
  title = {{Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32935},
}

@inproceedings{icml2026_variational_50105,
  title = {{Variational Inference for Uncertain Optimal Transport via Sinkhorn Parametrization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=93zkGLrp6P},
}

@inproceedings{icml2026_particles_54273,
  title = {{Particles Don’t Care About Z: Towards Scaling Entropy Estimation of Unnormalized Densities}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=nVAU1aVLtY},
}

@inproceedings{iclr2025_flow_83722,
  title = {{Flow-based Variational Mutual Information: Fast and Flexible Approximations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28097},
}

@inproceedings{cvpr2026_variational_96317,
  title = {{Variational Graph-based Normal Integration}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Chen_Variational_Graph-based_Normal_Integration_CVPR_2026_paper.html},
}