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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
Approximation Based Variance Reduction for Reparameterization Gradients Tomas Geffner Justin Domke BDL DRL 73 10 0 29 Jul 2020
Accounting for missing actors in interaction network inference from abundance data Raphaelle Momal Stephane S. Robin Christophe Ambroise CML 45 5 0 28 Jul 2020
$Generative networks as inverse problems with fractional wavelet scattering networks$ Generative networks as inverse problems with fractional wavelet scattering networks Jiasong Wu Jing Zhang Fuzhi Wu Youyong Kong Guanyu Yang L. Senhadji H. Shu GAN 49 1 0 28 Jul 2020
Online neural connectivity estimation with ensemble stimulation A. Draelos Eva A. Naumann John M. Pearson 90 5 0 27 Jul 2020
Disentangling the Gauss-Newton Method and Approximate Inference for Neural Networks Alexander Immer BDL 46 4 0 21 Jul 2020
Mixture Representation Learning with Coupled Autoencoders Yeganeh M. Marghi Rohan Gala U. Sümbül BDL 25 0 0 20 Jul 2020
Semi Conditional Variational Auto-Encoder for Flow Reconstruction and Uncertainty Quantification from Limited Observations K. Gundersen A. Oleynik N. Blaser G. Alendal BDL 75 29 0 19 Jul 2020
Probabilistic Active Meta-Learning Jean Kaddour Steindór Sæmundsson M. Deisenroth 98 35 0 17 Jul 2020
Deep Learning in Protein Structural Modeling and Design Wenhao Gao S. Mahajan Jeremias Sulam Jeffrey J. Gray 89 161 0 16 Jul 2020
The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction Alice Martin Charles Ollion Florian Strub Sylvain Le Corff Olivier Pietquin 55 6 0 15 Jul 2020
Measurement error models: from nonparametric methods to deep neural networks Zhirui Hu Z. Ke Jun S. Liu 26 4 0 15 Jul 2020
Deep composition of tensor-trains using squared inverse Rosenblatt transports Tiangang Cui S. Dolgov OT 57 34 0 14 Jul 2020
A Class of Conjugate Priors for Multinomial Probit Models which Includes the Multivariate Normal One A. Fasano Daniele Durante 76 27 0 14 Jul 2020
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users Laurent Valentin Jospin Wray Buntine F. Boussaïd Hamid Laga Bennamoun OOD BDL UQCV 99 636 0 14 Jul 2020
Dynamics of coordinate ascent variational inference: A case study in 2D Ising models Sean Plummer D. Pati A. Bhattacharya 109 21 0 13 Jul 2020
Bridging Maximum Likelihood and Adversarial Learning via $α$ -Divergence Miaoyun Zhao Yulai Cong Shuyang Dai Lawrence Carin GAN 58 10 0 13 Jul 2020
Estimating Stochastic Poisson Intensities Using Deep Latent Models Ruixin Wang Prateek Jaiswal Harsha Honnappa 38 7 0 12 Jul 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 75 20 0 10 Jul 2020
Robust Bayesian Classification Using an Optimistic Score Ratio Viet Anh Nguyen Nian Si Jose H. Blanchet 84 13 0 08 Jul 2020
Fast Bayesian Estimation of Spatial Count Data Models P. Bansal Rico Krueger D. Graham 86 8 0 07 Jul 2020
Qualitative Analysis of Monte Carlo Dropout Ronald Seoh UQCV BDL 52 29 0 03 Jul 2020
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference Rob Brekelmans Vaden Masrani Frank Wood Greg Ver Steeg Aram Galstyan 62 16 0 01 Jul 2020
Multi-Task Variational Information Bottleneck Weizhu Qian Bowei Chen Yichao Zhang Guanghui Wen Franck Gechter 79 11 0 01 Jul 2020
Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport Gonzalo E. Mena Amin Nejatbakhsh E. Varol Jonathan Niles-Weed OT 21 13 0 30 Jun 2020
VAE-KRnet and its applications to variational Bayes Xiaoliang Wan Shuangqing Wei BDL DRL 89 13 0 29 Jun 2020
Statistical Foundation of Variational Bayes Neural Networks Shrijita Bhattacharya T. Maiti BDL 47 11 0 29 Jun 2020
Non-Stationary Multi-layered Gaussian Priors for Bayesian Inversion M. Emzir Sari Lasanen Z. Purisha L. Roininen Simo Särkkä 80 9 0 28 Jun 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 74 22 0 26 Jun 2020
Neural Decomposition: Functional ANOVA with Variational Autoencoders Kaspar Märtens C. Yau DRL 33 10 0 25 Jun 2020
Stratified stochastic variational inference for high-dimensional network factor model E. Aliverti Massimiliano Russo BDL 58 8 0 25 Jun 2020
Fast, Optimal, and Targeted Predictions using Parametrized Decision Analysis Daniel R. Kowal 47 0 0 23 Jun 2020
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors Yuling Yao Aki Vehtari Andrew Gelman 100 63 0 22 Jun 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 82 211 0 22 Jun 2020
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data Martin Jørgensen Søren Hauberg 66 7 0 21 Jun 2020
Towards Adaptive Benthic Habitat Mapping J. Shields Oscar Pizarro Stefan B. Williams 47 15 0 20 Jun 2020
Constraining Variational Inference with Geometric Jensen-Shannon Divergence J. Deasy Nikola Simidjievski Pietro Lio DRL 91 30 0 18 Jun 2020
DrNAS: Dirichlet Neural Architecture Search Xiangning Chen Ruochen Wang Minhao Cheng Xiaocheng Tang Cho-Jui Hsieh OOD 107 103 0 18 Jun 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization Abhinav Agrawal Daniel Sheldon Justin Domke TPM BDL 114 41 0 18 Jun 2020
On the Variational Posterior of Dirichlet Process Deep Latent Gaussian Mixture Models Amine Echraibi Joachim Flocon-Cholet Stéphane Gosselin Sandrine Vaton BDL 31 4 0 16 Jun 2020
PAC-Bayesian Generalization Bounds for MultiLayer Perceptrons Xinjie Lan Xin Guo Kenneth Barner 47 3 0 16 Jun 2020
Variational Bayesian Monte Carlo with Noisy Likelihoods Luigi Acerbi 102 42 0 15 Jun 2020
Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning Yunhao Tang A. Kucukelbir OffRL 68 16 0 13 Jun 2020
Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections Csaba Tóth Patric Bonnier Harald Oberhauser AI4TS 87 14 0 12 Jun 2020
Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables Miguel Lázaro-Gredilla Wolfgang Lehrach Nishad Gothoskar Guangyao Zhou Antoine Dedieu Dileep George TPM 57 1 0 11 Jun 2020
Conditional Sampling with Monotone GANs: from Generative Models to Likelihood-Free Inference Ricardo Baptista Bamdad Hosseini Nikola B. Kovachki Youssef Marzouk OT GAN 109 24 0 11 Jun 2020
Bayesian Probabilistic Numerical Integration with Tree-Based Models Harrison Zhu Xing Liu Ruya Kang Zhichao Shen Seth Flaxman F. Briol TPM 42 5 0 09 Jun 2020
Wat zei je? Detecting Out-of-Distribution Translations with Variational Transformers Tim Z. Xiao Aidan Gomez Y. Gal UQLM 92 35 0 08 Jun 2020
Variational Variance: Simple, Reliable, Calibrated Heteroscedastic Noise Variance Parameterization Andrew Stirn David A. Knowles DRL 92 10 0 08 Jun 2020
A Survey of Bayesian Statistical Approaches for Big Data Farzana Jahan Insha Ullah Kerrie Mengersen 102 14 0 08 Jun 2020
Improving Inference for Neural Image Compression Yibo Yang Robert Bamler Stephan Mandt 97 123 0 07 Jun 2020