black-box variational inference

Batch, match, and patch: low-rank approximations for score-based variational inference AISTATS 2025 Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors AAAI 2025 A Framework for Improving the Reliability of Black-box Variational Inference JMLR 2024 Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds AISTATS 2024 Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box JMLR 2024 Efficient Mixture Learning in Black-Box Variational Inference ICML 2024 EigenVI: score-based variational inference with orthogonal function expansions NeurIPS 2024 Provably Scalable Black-Box Variational Inference with Structured Variational Families ICML 2024 On the Convergence of Black-Box Variational Inference NeurIPS 2023 Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference ICML 2023 Challenges and Opportunities in High Dimensional Variational Inference NeurIPS 2021 Marginalized Stochastic Natural Gradients for Black-Box Variational Inference ICML 2021 A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning Interspeech 2020 Robust, Accurate Stochastic Optimization for Variational Inference NeurIPS 2020 Boosting Black Box Variational Inference NeurIPS 2018 Variance Reduction in Black-box Variational Inference by Adaptive Importance Sampling IJCAI 2018 Fast Black-box Variational Inference through Stochastic Trust-Region Optimization NeurIPS 2017 Perturbative Black Box Variational Inference NeurIPS 2017 Black-Box Policy Search with Probabilistic Programs AISTATS 2016 Hierarchical Variational Models ICML 2016 Local Expectation Gradients for Black Box Variational Inference NeurIPS 2015 Black Box Variational Inference AISTATS 2014