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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
Bounding Wasserstein distance with couplings N. Biswas Lester W. Mackey 84 8 0 06 Dec 2021
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery Chris Cundy Aditya Grover Stefano Ermon CML 95 72 0 06 Dec 2021
Toward a Taxonomy of Trust for Probabilistic Machine Learning Tamara Broderick Andrew Gelman Rachael Meager Anna L. Smith Tian Zheng 82 11 0 05 Dec 2021
Counterfactual Explanations via Latent Space Projection and Interpolation Brian Barr Matthew R. Harrington Samuel Sharpe Capital One BDL 70 10 0 02 Dec 2021
Bayesian Modelling of Multivalued Power Curves from an Operational Wind Farm L. Bull P. Gardner T. Rogers N. Dervilis E. Cross E. Papatheou A. E. Maguire C. Campos K. Worden 47 13 0 30 Nov 2021
Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features Lars Henry Berge Olsen I. Glad Martin Jullum K. Aas TDI FAtt 109 17 0 26 Nov 2021
A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors Shivendra Agrawal Hwanwoo Kim D. Sanz-Alonso A. Strang 88 10 0 26 Nov 2021
BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule Miao Zhang Jilin Hu Steven W. Su Shirui Pan Xiaojun Chang B. Yang Gholamreza Haffari OOD 115 15 0 25 Nov 2021
Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data Vaidotas Šimkus Benjamin Rhodes Michael U. Gutmann 60 9 0 25 Nov 2021
Low-rank variational Bayes correction to the Laplace method J. van Niekerk Haavard Rue BDL 81 15 0 25 Nov 2021
Uncertainty estimation under model misspecification in neural network regression Maria R. Cervera Rafael Dätwyler Francesco DÁngelo Hamza Keurti Benjamin Grewe Christian Henning 64 6 0 23 Nov 2021
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning Zhaolin Ren Tianjun Zhang Csaba Szepesvári Bo Dai 115 20 0 22 Nov 2021
HTMOT : Hierarchical Topic Modelling Over Time Judicael Poumay A. Ittoo 57 3 0 22 Nov 2021
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel Yindong Chen Yiwei Wang Lulu Kang Chun Liu 131 2 0 21 Nov 2021
Gaussian Process Inference Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits Hao Chen Lili Zheng Raed Al Kontar Garvesh Raskutti 86 3 0 19 Nov 2021
Policy Gradient Approach to Compilation of Variational Quantum Circuits David A. Herrera-Martí 78 3 0 19 Nov 2021
Learn Quasi-stationary Distributions of Finite State Markov Chain Zhiqiang Cai Ling Lin Xiang Zhou BDL OffRL 26 1 0 19 Nov 2021
Locally Learned Synaptic Dropout for Complete Bayesian Inference Kevin L McKee Ian C Crandell Rishidev Chaudhuri R. C. O'Reilly 16 2 0 18 Nov 2021
CSI Clustering with Variational Autoencoding Michael Baur M. Würth M. Koller V. Andrei Wolfgang Utschick DRL 57 2 0 18 Nov 2021
Implicit copula variational inference M. Smith Rubén Loaiza-Maya 55 7 0 18 Nov 2021
Robustness of Bayesian Neural Networks to White-Box Adversarial Attacks Adaku Uchendu Daniel Campoy Christopher Menart Alexandra Hildenbrandt BDL AAML 114 5 0 16 Nov 2021
MoRe-Fi: Motion-robust and Fine-grained Respiration Monitoring via Deep-Learning UWB Radar Tianyue Zheng Zhe Chen Shujie Zhang Chao Cai Jun Luo 76 100 0 16 Nov 2021
Versatile Inverse Reinforcement Learning via Cumulative Rewards Niklas Freymuth P. Becker Gerhard Neumann 57 4 0 15 Nov 2021
On-the-Fly Rectification for Robust Large-Vocabulary Topic Inference Moontae Lee Sungjun Cho Kun Dong David M. Mimno D. Bindel 126 1 0 12 Nov 2021
Statistical Perspectives on Reliability of Artificial Intelligence Systems Yili Hong J. Lian Li Xu Jie Min Yueyao Wang Laura J. Freeman Xinwei Deng 68 33 0 09 Nov 2021
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning Raed Al Kontar Naichen Shi Xubo Yue Seokhyun Chung E. Byon ... Chinedum Okwudire Garvesh Raskutti R. Saigal Karandeep Singh Ye Zhisheng FedML 112 53 0 09 Nov 2021
Double Control Variates for Gradient Estimation in Discrete Latent Variable Models Michalis K. Titsias Jiaxin Shi BDL DRL 52 5 0 09 Nov 2021
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes Hugh Dance Brooks Paige GP 74 10 0 08 Nov 2021
Variational Inference with Holder Bounds Junya Chen Danni Lu Zidi Xiu Ke Bai Lawrence Carin Chenyang Tao 54 6 0 04 Nov 2021
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series Daniel Kramer P. Bommer Carlo Tombolini G. Koppe Daniel Durstewitz BDL AI4TS AI4CE 150 20 0 04 Nov 2021
Spatio-Temporal Variational Gaussian Processes Oliver Hamelijnck William J. Wilkinson Niki A. Loppi Arno Solin Theodoros Damoulas AI4TS 80 35 0 02 Nov 2021
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees William J. Wilkinson Simo Särkkä Arno Solin BDL 98 16 0 02 Nov 2021
A derivation of variational message passing (VMP) for latent Dirichlet allocation (LDA) Rebecca M. C. Taylor D. Coetsee J. D. Preez 25 0 0 02 Nov 2021
Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning Wanggang Shen Xun Huan 66 40 0 28 Oct 2021
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data Zhibo Zhu Ziqi Liu Ge Jin Qing Cui Lei Chen Jun Zhou Jianyong Zhou AI4TS 70 15 0 27 Oct 2021
Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence Henry Lam Haofeng Zhang 73 4 0 23 Oct 2021
Generative Networks for Precision Enthusiasts A. Butter Theo Heimel Sander Hummerich Tobias Krebs Tilman Plehn Armand Rousselot Sophia Vent AI4CE 82 60 0 22 Oct 2021
Variational Bayesian Approximation of Inverse Problems using Sparse Precision Matrices Jan Povala Ieva Kazlauskaite Eky Febrianto F. Cirak Mark Girolami 91 23 0 22 Oct 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 193 207 0 21 Oct 2021
Bayesian Meta-Learning Through Variational Gaussian Processes Vivek Myers Nikhil Sardana BDL UQCV 36 5 0 21 Oct 2021
Estimating the Arc Length of the Optimal ROC Curve and Lower Bounding the Maximal AUC Song Liu 27 0 0 18 Oct 2021
Interpolating between sampling and variational inference with infinite stochastic mixtures Richard D. Lange Ari S. Benjamin Ralf M. Haefner Xaq Pitkow 61 7 0 18 Oct 2021
Centroid Approximation for Bootstrap: Improving Particle Quality at Inference Mao Ye Qiang Liu 52 1 0 17 Oct 2021
Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution Yunshi Huang Émilie Chouzenoux J. Pesquet BDL 81 12 0 14 Oct 2021
Sparse Linear Mixed Model Selection via Streamlined Variational Bayes Emanuele Degani Luca Maestrini Dorota Toczydlowska M. Wand 59 1 0 13 Oct 2021
Challenges for Unsupervised Anomaly Detection in Particle Physics Katherine Fraser S. Homiller Rashmish K. Mishra B. Ostdiek M. Schwartz DRL 73 45 0 13 Oct 2021
Nonnegative spatial factorization F. W. Townes Barbara E. Engelhardt 42 11 0 12 Oct 2021
Information Theoretic Structured Generative Modeling Bo Hu Shujian Yu José C. Príncipe SyDa DRL 65 0 0 12 Oct 2021
Fitting large mixture models using stochastic component selection Milan Papez Tomás Pevný Václav Smídl 37 0 0 10 Oct 2021
Shift-BNN: Highly-Efficient Probabilistic Bayesian Neural Network Training via Memory-Friendly Pattern Retrieving Qiyu Wan Haojun Xia Xingyao Zhang Lening Wang Shuaiwen Leon Song Xin Fu OOD 66 9 0 07 Oct 2021