TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Papers/Automatic structured variational inference

Automatic structured variational inference

Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven

2020-02-03Variational Inference
PaperPDFCode(official)Code

Abstract

Stochastic variational inference offers an attractive option as a default method for differentiable probabilistic programming. However, the performance of the variational approach depends on the choice of an appropriate variational family. Here, we introduce automatic structured variational inference (ASVI), a fully automated method for constructing structured variational families, inspired by the closed-form update in conjugate Bayesian models. These convex-update families incorporate the forward pass of the input probabilistic program and can therefore capture complex statistical dependencies. Convex-update families have the same space and time complexity as the input probabilistic program and are therefore tractable for a very large family of models including both continuous and discrete variables. We validate our automatic variational method on a wide range of low- and high-dimensional inference problems. We find that ASVI provides a clear improvement in performance when compared with other popular approaches such as the mean-field approach and inverse autoregressive flows. We provide an open source implementation of ASVI in TensorFlow Probability.

Related Papers

Interpretable Bayesian Tensor Network Kernel Machines with Automatic Rank and Feature Selection2025-07-15Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference2025-06-26VHU-Net: Variational Hadamard U-Net for Body MRI Bias Field Correction2025-06-23Branching Stein Variational Gradient Descent for sampling multimodal distributions2025-06-16Robust Recursive Fusion of Multiresolution Multispectral Images with Location-Aware Neural Networks2025-06-16Variational Inference with Mixtures of Isotropic Gaussians2025-06-16Robust Filtering -- Novel Statistical Learning and Inference Algorithms with Applications2025-06-13Bayesian Probabilistic Matrix Factorization2025-06-11