Imagen de Portada

Provably Scalable Black-Box Variational Inference with Structured Variational Families

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ko, Joohwan, Kim, Kyurae, Kim, Woo Chang, Gardner, Jacob R.
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Computation
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?
por: Kim, Kyurae, et al.
Publicado: (2023)

On the Convergence of Black-Box Variational Inference
por: Kim, Kyurae, et al.
Publicado: (2023)

Nearly Dimension-Independent Convergence of Mean-Field Black-Box Variational Inference
por: Kim, Kyurae, et al.
Publicado: (2025)

Demystifying SGD with Doubly Stochastic Gradients
por: Kim, Kyurae, et al.
Publicado: (2024)

Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space
por: Kim, Kyurae, et al.
Publicado: (2026)

Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization
por: Kim, Kyurae, et al.
Publicado: (2025)

Stochastic Approximation with Biased MCMC for Expectation Maximization
por: Gruffaz, Samuel, et al.
Publicado: (2024)

Amortized Factor Inference Networks for Posterior Inference
por: Ko, Joohwan, et al.
Publicado: (2026)

Model-Informed Flows for Bayesian Inference
por: Ko, Joohwan, et al.
Publicado: (2025)

Understanding Stochastic Natural Gradient Variational Inference
por: Wu, Kaiwen, et al.
Publicado: (2024)

Latent Target Score Matching, with an application to Simulation-Based Inference
por: Ko, Joohwan, et al.
Publicado: (2026)

The Behavior and Convergence of Local Bayesian Optimization
por: Wu, Kaiwen, et al.
Publicado: (2023)

Efficient Mixture Learning in Black-Box Variational Inference
por: Hotti, Alexandra, et al.
Publicado: (2024)

Variance Control for Black Box Variational Inference Using The James-Stein Estimator
por: Dayta, Dominic B.
Publicado: (2024)

Adaptive Exponential Integration for Stable Gaussian Mixture Black-Box Variational Inference
por: Che, Baojun, et al.
Publicado: (2026)

Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box
por: Giordano, Ryan, et al.
Publicado: (2023)

Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix
por: Margossian, Charles C., et al.
Publicado: (2024)

Purely Agent-Driven Black-Box Optimization for Biological Design
por: Maus, Natalie, et al.
Publicado: (2026)

Variational Transdimensional Inference
por: Davies, Laurence, et al.
Publicado: (2025)

Approximation-Aware Bayesian Optimization
por: Maus, Natalie, et al.
Publicado: (2024)

Pathwise Gradient Variance Reduction with Control Variates in Variational Inference
por: Ng, Kenyon, et al.
Publicado: (2024)

BOOOM: Loss-Function-Agnostic Black-Box Optimization over Orthonormal Manifolds for Machine Learning and Statistical Inference
por: Kim, Beomchang, et al.
Publicado: (2026)

Structured Optimal Variational Inference for Dynamic Latent Space Models
por: Zhao, Peng, et al.
Publicado: (2022)

A Memetic Algorithm based on Variational Autoencoder for Black-Box Discrete Optimization with Epistasis among Parameters
por: Kato, Aoi, et al.
Publicado: (2025)

GLOVA: Global and Local Variation-Aware Analog Circuit Design with Risk-Sensitive Reinforcement Learning
por: Kim, Dongjun, et al.
Publicado: (2025)

Deep Variational Bayesian Modeling of Haze Degradation Process
por: Im, Eun Woo, et al.
Publicado: (2024)

Variational Inference for Bayesian MIDAS Regression
por: Simeone, Luigi
Publicado: (2026)

Modeling Choice via Self-Attention
por: Ko, Joohwan, et al.
Publicado: (2023)

Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
por: Margossian, Charles C., et al.
Publicado: (2024)

Large-scale Score-based Variational Posterior Inference for Bayesian Deep Neural Networks
por: Kim, Minyoung
Publicado: (2026)

Even More Guarantees for Variational Inference in the Presence of Symmetries
por: Zellinger, Lena, et al.
Publicado: (2026)

Rotated Mean-Field Variational Inference and Iterative Gaussianization
por: Chen, Yifan, et al.
Publicado: (2025)

Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference
por: Jiang, Xiaoyu, et al.
Publicado: (2024)

Analysis of kinetic Langevin Monte Carlo under the stochastic exponential Euler discretization from underdamped all the way to overdamped
por: Kim, Kyurae, et al.
Publicado: (2025)

Brain-like Variational Inference
por: Vafaii, Hadi, et al.
Publicado: (2024)

Generalized Guarantees for Variational Inference in the Presence of Even and Elliptical Symmetry
por: Margossian, Charles C., et al.
Publicado: (2025)

Variational Inference Using Material Point Method
por: Huang, Yongchao
Publicado: (2024)

Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference
por: Samplawski, Colin, et al.
Publicado: (2025)

Variational Grey-Box Dynamics Matching
por: Singh, Gurjeet Sangra, et al.
Publicado: (2026)

FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
por: Qin, Juehang, et al.
Publicado: (2025)