Yes, but Did It Work?: Evaluating Variational Inference

7 February 2018

Papers citing "Yes, but Did It Work?: Evaluating Variational Inference"

23 / 23 papers shown

Title
STiL: Semi-supervised Tabular-Image Learning for Comprehensive Task-Relevant Information Exploration in Multimodal Classification Siyi Du Xinzhe Luo D. O’Regan Chen Qin 69 0 0 08 Mar 2025
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models Jinlin Lai Justin Domke Daniel Sheldon 38 0 0 31 Oct 2024
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
Amortized Bayesian Multilevel Models Daniel Habermann Marvin Schmitt Lars Kühmichel Andreas Bulling Stefan T. Radev Paul-Christian Bürkner 70 3 0 23 Aug 2024
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 53 0 0 22 Jul 2024
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms Måns Magnusson Jakob Torgander Paul-Christian Bürkner Lu Zhang Bob Carpenter Aki Vehtari 42 6 0 06 Jul 2024
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs C. Margossian Loucas Pillaud-Vivien Lawrence K. Saul UD 71 2 0 20 Mar 2024
A Heavy-Tailed Algebra for Probabilistic Programming Feynman T. Liang Liam Hodgkinson Michael W. Mahoney 20 3 0 15 Jun 2023
Provable convergence guarantees for black-box variational inference Justin Domke Guillaume Garrigos Robert Mansel Gower 18 18 0 04 Jun 2023
Variational Latent Branching Model for Off-Policy Evaluation Qitong Gao Ge Gao Min Chi Miroslav Pajic OffRL 36 6 0 28 Jan 2023
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images Matthew D. Hoffman T. Le Pavel Sountsov Christopher Suter Ben Lee Vikash K. Mansinghka Rif A. Saurous BDL 29 12 0 27 Oct 2022
Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport Liyi Zhang David M. Blei C. A. Naesseth 30 6 0 03 Feb 2022
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 39 26 0 20 Dec 2021
Validating Gaussian Process Models with Simulation-Based Calibration John Mcleod F. Simpson 24 3 0 27 Oct 2021
Pathfinder: Parallel quasi-Newton variational inference Lu Zhang Bob Carpenter A. Gelman Aki Vehtari 43 40 0 09 Aug 2021
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence Ghassen Jerfel S. Wang Clara Fannjiang Katherine A. Heller Yi Ma Michael I. Jordan BDL 24 40 0 30 Jun 2021
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors Yuling Yao Aki Vehtari Andrew Gelman 29 60 0 22 Jun 2020
Variational Bayesian Monte Carlo with Noisy Likelihoods Luigi Acerbi 22 40 0 15 Jun 2020
The role of exchangeability in causal inference O. Saarela D. Stephens E. Moodie 36 5 0 02 Jun 2020
Assessment and adjustment of approximate inference algorithms using the law of total variance Xue Yu David J. Nott Minh-Ngoc Tran Nadja Klein 14 15 0 20 Nov 2019
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network Oscar Chang Yuling Yao David Williams-King Hod Lipson BDL UQCV 32 8 0 23 May 2019
Calibration procedures for approximate Bayesian credible sets J. Lee Geoff K. Nicholls Robin J. Ryder 6 13 0 15 Oct 2018
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with $β$ -Divergences Jeremias Knoblauch Jack Jewson Theodoros Damoulas 19 56 0 06 Jun 2018