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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
Conditionally structured variational Gaussian approximation with importance weights Linda S. L. Tan Aishwarya Bhaskaran David J. Nott 125 13 0 21 Apr 2019
Design of Communication Systems using Deep Learning: A Variational Inference Perspective Vishnu Raj Sheetal Kalyani 94 23 0 18 Apr 2019
An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning Yaoyao Liu Bernt Schiele Qianru Sun BDL 146 128 0 17 Apr 2019
High-dimensional copula variational approximation through transformation M. Smith Rubén Loaiza-Maya David J. Nott 79 33 0 16 Apr 2019
Copula-like Variational Inference Marcel Hirt P. Dellaportas Alain Durmus 42 5 0 15 Apr 2019
Variational Bayes for high-dimensional linear regression with sparse priors Kolyan Ray Botond Szabó 82 99 0 15 Apr 2019
Connections Between Adaptive Control and Optimization in Machine Learning Joseph E. Gaudio T. Gibson Anuradha M. Annaswamy M. Bolender E. Lavretsky AI4CE 29 44 0 11 Apr 2019
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features Arno Solin Manon Kok 74 23 0 10 Apr 2019
Learning Attribute Patterns in High-Dimensional Structured Latent Attribute Models Yuqi Gu Gongjun Xu 65 24 0 08 Apr 2019
Bayesian Estimation of Mixed Multinomial Logit Models: Advances and Simulation-Based Evaluations P. Bansal Rico Krueger M. Bierlaire Ricardo A. Daziano T. Rashidi 31 32 0 07 Apr 2019
Combining Sentiment Lexica with a Multi-View Variational Autoencoder Alexander Miserlis Hoyle Lawrence Wolf-Sonkin Hanna M. Wallach Ryan Cotterell Isabelle Augenstein 50 9 0 05 Apr 2019
A deterministic and computable Bernstein-von Mises theorem Guillaume P. Dehaene 72 14 0 04 Apr 2019
dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences J. Speagle 88 1,223 0 03 Apr 2019
The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records Linying Zhang Yixin Wang A. Ostropolets J. J. Mulgrave David M. Blei G. Hripcsak BDL CML 136 1 0 03 Apr 2019
Identification, Interpretability, and Bayesian Word Embeddings Adam M. Lauretig BDL 42 11 0 02 Apr 2019
Unsupervised Contextual Anomaly Detection using Joint Deep Variational Generative Models Yaniv Shulman DRL 28 6 0 01 Apr 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems Laura von Rueden S. Mayer Katharina Beckh B. Georgiev Sven Giesselbach ... Rajkumar Ramamurthy Michal Walczak Jochen Garcke Christian Bauckhage Jannis Schuecker 157 653 0 29 Mar 2019
Variational Bayesian modelling of mixed-effects J. Daunizeau 8 4 0 21 Mar 2019
Performance Measurement for Deep Bayesian Neural Network Yikuan Li Yajie Zhu BDL OOD UQCV 27 1 0 20 Mar 2019
A semi-supervised deep learning algorithm for abnormal EEG identification Subhrajit Roy Kiran Kate Martin Hirzel 24 3 0 19 Mar 2019
Pairwise Comparisons with Flexible Time-Dynamics Lucas Maystre Victor Kristof Matthias Grossglauser SyDa 25 0 0 18 Mar 2019
Approximating exponential family models (not single distributions) with a two-network architecture Sean R. Bittner John P. Cunningham 46 4 0 18 Mar 2019
What You Say and How You Say it: Joint Modeling of Topics and Discourse in Microblog Conversations Jichuan Zeng Jing Li Yulan He Cuiyun Gao Michael R. Lyu Irwin King BDL 45 27 0 18 Mar 2019
GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection Q. Nguyen Kar Wai Lim D. Divakaran K. H. Low M. Chan DRL 68 137 0 15 Mar 2019
Deep Switch Networks for Generating Discrete Data and Language Payam Delgosha Naveen Goela 23 0 0 14 Mar 2019
Learning Latent Representations of Bank Customers With The Variational Autoencoder R. A. Mancisidor Michael C. Kampffmeyer K. Aas Robert Jenssen DRL BDL 33 25 0 14 Mar 2019
Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy Yunhao Tang Mingzhang Yin Mingyuan Zhou 21 0 0 13 Mar 2019
On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making Prateek Jaiswal Harsha Honnappa Vinayak A. Rao 40 2 0 12 Mar 2019
Elements of Sequential Monte Carlo C. A. Naesseth Fredrik Lindsten Thomas B. Schon 75 97 0 12 Mar 2019
A cross-center smoothness prior for variational Bayesian brain tissue segmentation Wouter M. Kouw S. Ørting Jens Petersen K. S. Pedersen Marleen de Bruijne 65 8 0 11 Mar 2019
$β^3$ -IRT: A New Item Response Model and its Applications Yu Chen Telmo de Menezes e Silva Filho R. Prudêncio Tom Diethe Peter A. Flach 144 30 0 10 Mar 2019
Imputation estimators for unnormalized models with missing data Masatoshi Uehara Takeru Matsuda Jae Kwang Kim 37 7 0 08 Mar 2019
Based on Graph-VAE Model to Predict Student's Score Yang Zhang Ming-choa Lu 13 0 0 08 Mar 2019
Streamlined Computing for Variational Inference with Higher Level Random Effects T. Nolan M. Menictas M. Wand 32 14 0 07 Mar 2019
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models Yuanshuo Zhou Bradley Gram-Hansen Tobias Kohn Tom Rainforth Hongseok Yang Frank Wood 80 25 0 06 Mar 2019
Probabilistic Modeling for Novelty Detection with Applications to Fraud Identification Rémi Domingues AAML 40 3 0 05 Mar 2019
Empirical priors for prediction in sparse high-dimensional linear regression Ryan Martin Yiqi Tang 211 21 0 03 Mar 2019
Approximation Properties of Variational Bayes for Vector Autoregressions Reza Hajargasht BDL 26 1 0 02 Mar 2019
The principles of adaptation in organisms and machines I: machine learning, information theory, and thermodynamics Hideaki Shimazaki DRL AI4CE 19 6 0 28 Feb 2019
Variational Inference to Measure Model Uncertainty in Deep Neural Networks K. Posch J. Steinbrener J. Pilz UQCV BDL 58 29 0 26 Feb 2019
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era N. Durrande Vincent Adam L. Bordeaux Stefanos Eleftheriadis J. Hensman 76 26 0 26 Feb 2019
A Nonparametric Multi-view Model for Estimating Cell Type-Specific Gene Regulatory Networks Cassandra Burdziak E. Azizi Sandhya Prabhakaran Dana Peér 26 14 0 21 Feb 2019
Multifidelity Bayesian Optimization for Binomial Output L. Matyushin Alexey Zaytsev O. Alenkin Andrey Ustuzhanin 24 0 0 19 Feb 2019
Divergence-Based Motivation for Online EM and Combining Hidden Variable Models Ehsan Amid Manfred K. Warmuth 57 4 0 11 Feb 2019
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime Constantin Grigo P. Koutsourelakis AI4CE 131 26 0 11 Feb 2019
Estimating the Rate Constant from Biosensor Data via an Adaptive Variational Bayesian Approach Y. Zhang Z. Yao P. Forssén T. Fornstedt 25 5 0 11 Feb 2019
Manifold Optimization Assisted Gaussian Variational Approximation Bingxin Zhou Junbin Gao Minh-Ngoc Tran Richard Gerlach 67 6 0 11 Feb 2019
A stochastic version of Stein Variational Gradient Descent for efficient sampling Lei Li Yingzhou Li Jian‐Guo Liu Zibu Liu Jianfeng Lu 63 35 0 09 Feb 2019
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap Edwin Fong Simon Lyddon Chris Holmes 184 36 0 08 Feb 2019
Meta-Amortized Variational Inference and Learning Mike Wu Kristy Choi Noah D. Goodman Stefano Ermon OOD VLM BDL DRL 84 36 0 05 Feb 2019