Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space

10 April 2023

Michael Diao

Krishnakumar Balasubramanian

Papers citing "Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space"

20 / 20 papers shown

Title
Non-geodesically-convex optimization in the Wasserstein space Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Petrus Mikkola Marcelo Hartmann Kai Puolamaki Arto Klami 53 2 0 08 Jan 2025
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix C. Margossian Lawrence K. Saul 31 1 0 14 Oct 2024
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Marcelo Hartmann Arto Klami DRL 34 0 0 03 Oct 2024
Optimal sequencing depth for single-cell RNA-sequencing in Wasserstein space Jakwang Kim Sharvaj Kubal Geoffrey Schiebinger 24 1 0 22 Sep 2024
On Naive Mean-Field Approximation for high-dimensional canonical GLMs S. Mukherjee Jiaze Qiu Subhabrata Sen 24 1 0 21 Jun 2024
Proximal Interacting Particle Langevin Algorithms Paula Cordero Encinar F. R. Crucinio O. Deniz Akyildiz 25 3 0 20 Jun 2024
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians Tom Huix Anna Korba Alain Durmus Eric Moulines 28 7 0 06 Jun 2024
You Only Accept Samples Once: Fast, Self-Correcting Stochastic Variational Inference Dominic B. Dayta TPM BDL 28 0 0 05 Jun 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 26 9 0 22 Feb 2024
Sampling from the Mean-Field Stationary Distribution Yunbum Kook Matthew Shunshi Zhang Sinho Chewi Murat A. Erdogdu Mufan Bill Li 56 7 0 12 Feb 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 27 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 29 7 0 05 Dec 2023
Bridging the Gap Between Variational Inference and Wasserstein Gradient Flows Mingxuan Yi Song Liu DRL 20 8 0 31 Oct 2023
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space Xiuyuan Cheng Jianfeng Lu Yixin Tan Yao Xie 106 15 0 26 Oct 2023
A Mean Field Approach to Empirical Bayes Estimation in High-dimensional Linear Regression S. Mukherjee Bodhisattva Sen Subhabrata Sen 32 4 0 28 Sep 2023
Provable convergence guarantees for black-box variational inference Justin Domke Guillaume Garrigos Robert Mansel Gower 18 18 0 04 Jun 2023
On the Convergence of Black-Box Variational Inference Kyurae Kim Jisu Oh Kaiwen Wu Yi-An Ma J. Gardner BDL 40 15 0 24 May 2023
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent Tianle Liu Promit Ghosal Krishnakumar Balasubramanian Natesh S. Pillai 19 9 0 23 May 2023
On the Approximation Accuracy of Gaussian Variational Inference A. Katsevich Philippe Rigollet 23 17 0 05 Jan 2023
Fast Differentiable Matrix Square Root and Inverse Square Root Yue Song N. Sebe Wei Wang 27 15 0 29 Jan 2022