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Variational Inference: A Review for Statisticians

4 January 2016

Papers citing "Variational Inference: A Review for Statisticians"

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Title
Latent Network Estimation and Variable Selection for Compositional Data via Variational EM Nathan Osborne Christine B. Peterson M. Vannucci BDL 64 19 0 25 Oct 2020
Statistical optimality and stability of tangent transform algorithms in logit models I. Ghosh A. Bhattacharya D. Pati 37 3 0 25 Oct 2020
Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors Jincheng Bai Qifan Song Guang Cheng BDL 49 4 0 24 Oct 2020
Variational Bayesian Unlearning Q. Nguyen Bryan Kian Hsiang Low Patrick Jaillet BDL MU 98 128 0 24 Oct 2020
Measure Transport with Kernel Stein Discrepancy Matthew A. Fisher T. Nolan Matthew M. Graham D. Prangle Chris J. Oates OT 124 15 0 22 Oct 2020
Spike and slab variational Bayes for high dimensional logistic regression Kolyan Ray Botond Szabó Gabriel Clara 97 29 0 22 Oct 2020
Probabilistic Circuits for Variational Inference in Discrete Graphical Models Andy Shih Stefano Ermon TPM 65 22 0 22 Oct 2020
Bayesian Attention Modules Xinjie Fan Shujian Zhang Bo Chen Mingyuan Zhou 183 62 0 20 Oct 2020
VarGrad: A Low-Variance Gradient Estimator for Variational Inference Lorenz Richter Ayman Boustati Nikolas Nusken Francisco J. R. Ruiz Ömer Deniz Akyildiz DRL 231 54 0 20 Oct 2020
Learning to Learn Variational Semantic Memory Xiantong Zhen Yingjun Du Huan Xiong Qiang Qiu Cees G. M. Snoek Ling Shao SSL BDL VLM DRL 74 36 0 20 Oct 2020
PAC $^m$ -Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime Warren Morningstar Alexander A. Alemi Joshua V. Dillon 132 16 0 19 Oct 2020
On the Difficulty of Unbiased Alpha Divergence Minimization Tomas Geffner Justin Domke 109 18 0 19 Oct 2020
Statistical Guarantees and Algorithmic Convergence Issues of Variational Boosting B. Guha A. Bhattacharya D. Pati 87 2 0 19 Oct 2020
Bayesian Inference for Optimal Transport with Stochastic Cost Anton Mallasto Markus Heinonen Samuel Kaski OT 84 1 0 19 Oct 2020
Directed Variational Cross-encoder Network for Few-shot Multi-image Co-segmentation Sayan Banerjee S. Bhat S. Chaudhuri R. Velmurugan 10 1 0 17 Oct 2020
Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning Chenjia Bai Peng Liu Kaiyu Liu Zhaoran Wang Yingnan Zhao Lingxiao Wang SSL 62 18 0 17 Oct 2020
Flexible mean field variational inference using mixtures of non-overlapping exponential families J. Spence 55 4 0 14 Oct 2020
Variational Approximation of Factor Stochastic Volatility Models David Gunawan Robert Kohn David J. Nott 53 7 0 13 Oct 2020
Using Bayesian deep learning approaches for uncertainty-aware building energy surrogate models Paul Westermann R. Evins AI4CE 46 44 0 05 Oct 2020
Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains Francisco J. R. Ruiz Michalis K. Titsias taylan. cemgil Arnaud Doucet BDL DRL 65 14 0 05 Oct 2020
Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices Nadja Klein M. Smith David J. Nott BDL AI4TS 54 27 0 05 Oct 2020
MCMC-Interactive Variational Inference Quan Zhang Huangjie Zheng Mingyuan Zhou 56 1 0 02 Oct 2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers Hanjie Chen Yangfeng Ji AAML VLM 109 66 0 01 Oct 2020
Sampling possible reconstructions of undersampled acquisitions in MR imaging K. Tezcan Neerav Karani Christian F. Baumgartner E. Konukoglu 32 9 0 30 Sep 2020
Targeted VAE: Variational and Targeted Learning for Causal Inference M. Vowels Necati Cihan Camgöz Richard Bowden BDL OOD CML 58 8 0 28 Sep 2020
f-Divergence Variational Inference Neng Wan Dapeng Li N. Hovakimyan 114 35 0 28 Sep 2020
A Variational Auto-Encoder for Reservoir Monitoring K. Gundersen S. Hosseini A. Oleynik G. Alendal 25 1 0 23 Sep 2020
Reward Maximisation through Discrete Active Inference Lancelot Da Costa Noor Sajid Thomas Parr Karl J. Friston Ryan Smith 90 4 0 17 Sep 2020
Clustering of non-Gaussian data by variational Bayes for normal inverse Gaussian mixture models T. Takekawa 13 1 0 13 Sep 2020
Generalized Multi-Output Gaussian Process Censored Regression Daniele Gammelli Kasper Pryds Rolsted Dario Pacino Filipe Rodrigues 43 14 0 10 Sep 2020
Convergence Rates of Empirical Bayes Posterior Distributions: A Variational Perspective Fengshuo Zhang Chao Gao 37 2 0 08 Sep 2020
Non-exponentially weighted aggregation: regret bounds for unbounded loss functions Pierre Alquier 105 19 0 07 Sep 2020
Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings John Mitros A. Pakrashi Brian Mac Namee UQCV 104 2 0 03 Sep 2020
Online Estimation and Community Detection of Network Point Processes for Event Streams Guanhua Fang Owen G. Ward Tian Zheng 38 3 0 03 Sep 2020
Scalable computation of predictive probabilities in probit models with Gaussian process priors JIAN-PENG Cao Daniele Durante M. Genton 87 11 0 03 Sep 2020
Quasi-symplectic Langevin Variational Autoencoder Zihao Wang H. Delingette BDL DRL 73 4 0 02 Sep 2020
Robust, Accurate Stochastic Optimization for Variational Inference Akash Kumar Dhaka Alejandro Catalina Michael Riis Andersen Maans Magnusson Jonathan H. Huggins Aki Vehtari 71 34 0 01 Sep 2020
Exoplanet Validation with Machine Learning: 50 new validated Kepler planets David J Armstrong Jevgenij Gamper Theodoros Damoulas 55 27 0 24 Aug 2020
Variational Autoencoder for Anti-Cancer Drug Response Prediction Hongyuan Dong Jiaqing Xie Zhi Jing Dexin Ren DRL 83 14 0 22 Aug 2020
Bayesian neural networks and dimensionality reduction Deborshee Sen Theodore Papamarkou David B. Dunson BDL 61 5 0 18 Aug 2020
Fast Approximate Bayesian Contextual Cold Start Learning (FAB-COST) Jack R. McKenzie Peter A. Appleby T. House N. Walton 25 0 0 18 Aug 2020
Joint Variational Autoencoders for Recommendation with Implicit Feedback Bahare Askari Jaroslaw Szlichta Amirali Salehi-Abari DRL 51 4 0 17 Aug 2020
Unifying supervised learning and VAEs -- coverage, systematics and goodness-of-fit in normalizing-flow based neural network models for astro-particle reconstructions T. Glüsenkamp 39 1 0 13 Aug 2020
Sampling using $SU(N)$ gauge equivariant flows D. Boyda G. Kanwar S. Racanière Danilo Jimenez Rezende M. S. Albergo Kyle Cranmer D. Hackett P. Shanahan 96 129 0 12 Aug 2020
Variational Bayes for Gaussian Factor Models under the Cumulative Shrinkage Process Sirio Legramanti 14 0 0 12 Aug 2020
Comparative Analysis of the Hidden Markov Model and LSTM: A Simulative Approach M. Tadayon G. Pottie BDL AI4TS 46 5 0 09 Aug 2020
Learning Insulin-Glucose Dynamics in the Wild Andrew C. Miller N. Foti E. Fox AI4TS 37 20 0 06 Aug 2020
Exploring Variational Deep Q Networks A. H. Bell-Thomas 20 0 0 04 Aug 2020
Gibbs sampler and coordinate ascent variational inference: a set-theoretical review Se Yoon Lee 46 33 0 03 Aug 2020
Variational approximations of empirical Bayes posteriors in high-dimensional linear models Yue Yang Ryan Martin 64 7 0 31 Jul 2020