% Key papers for Stein variational gradient descent (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2016_stein_56007,
  title = {{Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7009},
}

@inproceedings{neurips2017_stein_56686,
  title = {{Stein Variational Gradient Descent as Gradient Flow}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9096},
}

@inproceedings{neurips2019_stein_59021,
  title = {{Stein Variational Gradient Descent With Matrix-Valued Kernels}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13861},
}

@inproceedings{icml2016_black_35758,
  title = {{Black-Box Alpha Divergence Minimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/hernandez-lobatob16.html},
}

@inproceedings{neurips2018_a_56815,
  title = {{A Stein variational Newton method}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11874},
}

@inproceedings{aaai2018_riemannian_102543,
  title = {{Riemannian Stein Variational Gradient Descent for Bayesian Inference}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11810},
}

@inproceedings{neurips2020_a_59260,
  title = {{A Non-Asymptotic Analysis for Stein Variational Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17676},
}

@inproceedings{neurips2018_stein_57648,
  title = {{Stein Variational Gradient Descent as Moment Matching}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11845},
}

@inproceedings{neurips2020_projected_60625,
  title = {{Projected Stein Variational Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18863},
}

@inproceedings{icml2018_stein_37004,
  title = {{Stein Variational Gradient Descent Without Gradient}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2105},
}

@inproceedings{neurips2017_vae_56758,
  title = {{VAE Learning via Stein Variational Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9203},
}

@inproceedings{neurips2019_minimum_58605,
  title = {{Minimum Stein Discrepancy Estimators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14244},
}

@inproceedings{neurips2020_robust_60750,
  title = {{Robust, Accurate Stochastic Optimization for Variational Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17180},
}

@inproceedings{icml2019_quantile_37676,
  title = {{Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3796},
}

@inproceedings{neurips2021_profiling_62248,
  title = {{Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27336},
}

@inproceedings{icml2020_stochastic_38797,
  title = {{Stochastic Optimization for Regularized Wasserstein Estimators}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6517},
}

@inproceedings{icml2019_nonlinear_37584,
  title = {{Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3886},
}

@inproceedings{neurips2021_large_63138,
  title = {{Large-Scale Wasserstein Gradient Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27486},
}

@inproceedings{iclr2021_convex_30695,
  title = {{Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3181},
}

@inproceedings{icml2022_variational_41339,
  title = {{Variational Wasserstein gradient flow}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16823},
}

@inproceedings{icml2026_stochastic_49634,
  title = {{Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=4HquuQN4qK},
}

@inproceedings{neurips2024_semi_70797,
  title = {{Semi-Discrete Optimal Transport: Nearly Minimax Estimation With Stochastic Gradient Descent and Adaptive Entropic Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93687},
}

@inproceedings{neurips2025_decreasing_76431,
  title = {{Decreasing Entropic Regularization Averaged Gradient for Semi-Discrete Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=JHlBLb6Jpz},
}

@inproceedings{iclr2025_long_82472,
  title = {{Long-time asymptotics of noisy SVGD outside the population limit}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29322},
}

@inproceedings{iclr2025_improved_83704,
  title = {{Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28115},
}

@inproceedings{iclr2026_adaptive_84420,
  title = {{Adaptive gradient descent on Riemannian manifolds and its applications to Gaussian variational inference}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=2TTQjRkgFn},
}

@inproceedings{iclr2026_bayesian_87524,
  title = {{Bayesian Parameter Shift Rules in Variational Quantum Eigensolvers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=cS0L2kj0lj},
}