Provable Smoothness Guarantees for Black-Box Variational Inference

24 January 2019

Papers citing "Provable Smoothness Guarantees for Black-Box Variational Inference"

8 / 8 papers shown

Title
You Only Accept Samples Once: Fast, Self-Correcting Stochastic Variational Inference Dominic B. Dayta TPM BDL 32 0 0 05 Jun 2024
Demystifying SGD with Doubly Stochastic Gradients Kyurae Kim Joohwan Ko Yian Ma Jacob R. Gardner 53 0 0 03 Jun 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 35 7 0 05 Dec 2023
Provable convergence guarantees for black-box variational inference Justin Domke Guillaume Garrigos Robert Mansel Gower 28 18 0 04 Jun 2023
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent Tianle Liu Promit Ghosal Krishnakumar Balasubramanian Natesh S. Pillai 36 9 0 23 May 2023
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space Michael Diao Krishnakumar Balasubramanian Sinho Chewi Adil Salim BDL 32 21 0 10 Apr 2023
Regularized Rényi divergence minimization through Bregman proximal gradient algorithms Thomas Guilmeau Émilie Chouzenoux Victor Elvira 39 3 0 09 Nov 2022