On the Convergence of Black-Box Variational Inference

On the Convergence of Black-Box Variational Inference

24 May 2023

Jacob R. Gardner

Papers citing "On the Convergence of Black-Box Variational Inference"

19 / 19 papers shown

Title
Globally Convergent Variational Inference Declan McNamara J. Loper Jeffrey Regier 53 0 0 14 Jan 2025
Efficient Mixture Learning in Black-Box Variational Inference A. Hotti Oskar Kviman Ricky Molén Victor Elvira Jens Lagergren 49 1 0 11 Jun 2024
You Only Accept Samples Once: Fast, Self-Correcting Stochastic Variational Inference Dominic B. Dayta TPM BDL 30 0 0 05 Jun 2024
Understanding Stochastic Natural Gradient Variational Inference Kaiwen Wu Jacob R. Gardner BDL 56 1 0 04 Jun 2024
Demystifying SGD with Doubly Stochastic Gradients Kyurae Kim Joohwan Ko Yian Ma Jacob R. Gardner 53 0 0 03 Jun 2024
Understanding and mitigating difficulties in posterior predictive evaluation Abhinav Agrawal Justin Domke UQCV 45 0 0 30 May 2024
Kernel Semi-Implicit Variational Inference Ziheng Cheng Longlin Yu Tianyu Xie Shiyue Zhang Cheng Zhang 35 2 0 29 May 2024
Evaluating Bayesian deep learning for radio galaxy classification Devina Mohan Anna M. M. Scaife UQCV BDL 46 1 0 28 May 2024
Batch and match: black-box variational inference with a score-based divergence Diana Cai Chirag Modi Loucas Pillaud-Vivien C. Margossian Robert Mansel Gower David M. Blei Lawrence K. Saul 38 9 0 22 Feb 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 33 2 0 19 Jan 2024
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space Yiheng Jiang Sinho Chewi Aram-Alexandre Pooladian 32 7 0 05 Dec 2023
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? Kyurae Kim Yian Ma Jacob R. Gardner 34 5 0 27 Jul 2023
Noise Is Not the Main Factor Behind the Gap Between SGD and Adam on Transformers, but Sign Descent Might Be Frederik Kunstner Jacques Chen J. Lavington Mark W. Schmidt 40 67 0 27 Apr 2023
Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box Ryan Giordano Martin Ingram Tamara Broderick 61 12 0 11 Apr 2023
Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference Kyurae Kim Kaiwen Wu Jisu Oh Jacob R. Gardner BDL 26 7 0 18 Mar 2023
Regularized Rényi divergence minimization through Bregman proximal gradient algorithms Thomas Guilmeau Émilie Chouzenoux Victor Elvira 34 3 0 09 Nov 2022
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi Ma Tong Zhang 37 16 0 05 Oct 2021
Markovian Score Climbing: Variational Inference with KL(p\|\|q) C. A. Naesseth Fredrik Lindsten David M. Blei 121 54 0 23 Mar 2020
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,201 0 16 Aug 2016