JD
Justin Domke
cs.LGstat.MLAlgorithmsArtificial Intelligencecs.CVmath.OCstat.COcs.AIModels, Statisticalstat.ME
On Valency
published · living versionsW_x3fpm9vm·v1 · currentpublished
Stacking-Based Weighting for Large Language Bayes in M-Open Settings
with Anant Bhide, Akarsh Gupta, Edmond Cunningham
1 version
Preprints & journals
41 papers in the corpus · 2009–2026Amortized Factor Inference Networks for Posterior Inference2605.26419v2 · Joohwan Ko, Justin Domke2026 · 0 citationsarXiv
Model-Informed Flows for Bayesian Inference2505.24243v2 · Joohwan Ko, Justin Domke2025 · 0 citationsarXiv
Large Language Bayes2504.14025v2 · Justin Domke2025 · 0 citationsarXiv
Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI2412.08824v1 · Abhinav Agrawal, Justin Domke2024 · 0 citationsarXiv
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models2410.24079v3 · Jinlin Lai, Justin Domke, Daniel Sheldon2024 · 0 citationsarXiv
Understanding and mitigating difficulties in posterior predictive evaluation2405.19747v1 · Abhinav Agrawal, Justin Domke2024 · 0 citationsarXiv
Simulation-based stacking2310.17009v2 · Yuling Yao, Bruno R'egaldo-Saint Blancard, Justin Domke2023 · 0 citationsarXiv
Provable convergence guarantees for black-box variational inference2306.03638v3 · Justin Domke, Guillaume Garrigos, Robert Gower2023 · 3 citationsarXiv
Discriminative calibration: Check Bayesian computation from simulations and flexible classifier2305.14593v2 · Yuling Yao, Justin Domke2023 · 0 citationsarXiv
Sample Average Approximation for Black-Box VI2304.06803v2 · Javier Burroni, Justin Domke, Daniel Sheldon2023 · 1 citationarXiv
U-Statistics for Importance-Weighted Variational Inference2302.13918v1 · Javier Burroni, Kenta Takatsu, Justin Domke et al.2023 · 0 citationsarXiv
Joint control variate for faster black-box variational inference2210.07290v4 · Xi Wang, Tomas Geffner, Justin Domke2022 · 0 citationsarXiv
Langevin Diffusion Variational Inference2208.07743v2 · Tomas Geffner, Justin Domke2022 · 0 citationsarXiv
Variational Inference with Locally Enhanced Bounds for Hierarchical Models2203.04432v2 · Tomas Geffner, Justin Domke2022 · 0 citationsarXiv
Amortized Variational Inference for Simple Hierarchical Models2111.03144v1 · Abhinav Agrawal, Justin Domke2021 · 3 citationsarXiv
Variational Marginal Particle Filters2109.15134v3 · Jinlin Lai, Justin Domke, Daniel Sheldon2021 · 4 citationsarXiv
MCMC Variational Inference via Uncorrected Hamiltonian Annealing2107.04150v3 · Tomas Geffner, Justin Domke2021 · 2 citationsNeurIPS (2021)
Empirical Evaluation of Biased Methods for Alpha Divergence Minimization2105.06587v1 · Tomas Geffner, Justin Domke2021 · 3 citationsarXiv
An Easy to Interpret Diagnostic for Approximate Inference: Symmetric Divergence Over Simulations2103.01030v1 · Justin Domke2021 · 5 citationsarXiv
On the Difficulty of Unbiased Alpha Divergence Minimization2010.09541v4 · Tomas Geffner, Justin Domke2020 · 3 citationsICML 2021
Approximation Based Variance Reduction for Reparameterization Gradients2007.14634v2 · Tomas Geffner, Justin Domke2020 · 2 citationsarXiv
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization2006.10343v2 · Abhinav Agrawal, Daniel Sheldon, Justin Domke2020 · 3 citationsarXiv
Moment-Matching Conditions for Exponential Families with Conditioning or Hidden Data2001.09771v1 · Justin Domke2020 · 0 citationsarXiv
A Rule for Gradient Estimator Selection, with an Application to Variational Inference1911.01894v1 · Tomas Geffner, Justin Domke2019 · 1 citationarXiv
Thompson Sampling with Approximate Inference1908.04970v2 · My Phan, Yasin Abbasi-Yadkori, Justin Domke2019 · 9 citationsarXiv
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation1906.10115v3 · Justin Domke, Daniel Sheldon2019 · 6 citationsarXiv
Provable Gradient Variance Guarantees for Black-Box Variational Inference1906.08241v2 · Justin Domke2019 · 4 citationsarXiv
Provable Smoothness Guarantees for Black-Box Variational Inference1901.08431v4 · Justin Domke2019 · 7 citationsarXiv
Using Large Ensembles of Control Variates for Variational Inference1810.12482v2 · Tomas Geffner, Justin Domke2018 · 9 citationsarXiv
Importance Weighting and Variational Inference1808.09034v3 · Justin Domke, Daniel Sheldon2018 · 56 citationsarXiv
Conditional Inference in Pre-trained Variational Autoencoders via Cross-coding1805.07785v2 · Ga Wu, Justin Domke, Scott Sanner2018 · 4 citationsarXiv
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI1706.06529v1 · Justin Domke2017 · 1 citationarXiv
Clamping Improves TRW and Mean Field Approximations1510.00087v1 · Adrian Weller, Justin Domke2015 · 4 citationsarXiv
Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets1509.08992v2 · Justin Domke2015 · 1 citationarXiv
Projecting Markov Random Field Parameters for Fast Mixing1411.1119v3 · Xianghang Liu, Justin Domke2014 · 3 citationsarXiv
Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems1407.2710v1 · Aaron J. Defazio, Tib'erio S. Caetano, Justin Domke2014 · 117 citationsInternational Conference on Machine Learning 2014
Projecting Ising Model Parameters for Fast Mixing1407.0749v2 · Justin Domke, Xianghang Liu2014 · 5 citationsarXiv
Structured Learning via Logistic Regression1407.0754v1 · Justin Domke2014 · 5 citationsarXiv
Learning graphical model parameters with approximate marginal inference.23969389 · Domke, Justin2014 · 136 citationsIEEE transactions on pattern analysis and machine intelligence. 2013;35(10):2454-67
Learning Convex Inference of Marginals1206.3247v1 · Justin Domke2012 · 5 citationsarXiv
Image transformations and blurring.19299857 · Domke, Justin, Aloimonos, Yiannis2009 · 5 citationsIEEE transactions on pattern analysis and machine intelligence. 2009;31(5):811-23
Career total: 72 works. 41 are in this corpus.
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