Stochastic Variational Inference

29 June 2012

Matt Hoffman

Papers citing "Stochastic Variational Inference"

50 / 1,065 papers shown

Title
Topic Modeling in Embedding Spaces Adji Bousso Dieng Francisco J. R. Ruiz David M. Blei BDL 36 621 0 08 Jul 2019
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale A. G. Baydin Lei Shao W. Bhimji Lukas Heinrich Lawrence Meadows ... Philip Torr Victor W. Lee Kyle Cranmer P. Prabhat Frank Wood 28 55 0 08 Jul 2019
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks Qi She Anqi Wu BDL 26 34 0 01 Jul 2019
Hierarchical Optimal Transport for Document Representation Mikhail Yurochkin Sebastian Claici Edward Chien F. Mirzazadeh Justin Solomon OT 21 90 0 26 Jun 2019
An Unsupervised Bayesian Neural Network for Truth Discovery in Social Networks Jielong Yang Wee Peng Tay BDL 30 8 0 25 Jun 2019
Multi-task Learning for Aggregated Data using Gaussian Processes F. Yousefi M. Smith Mauricio A. Alvarez FedML 9 34 0 22 Jun 2019
Probabilistic Logic Neural Networks for Reasoning Meng Qu Jian Tang 30 160 0 20 Jun 2019
Provable Gradient Variance Guarantees for Black-Box Variational Inference Justin Domke DRL 9 21 0 19 Jun 2019
A Survey of Optimization Methods from a Machine Learning Perspective Shiliang Sun Zehui Cao Han Zhu Jing Zhao 22 549 0 17 Jun 2019
Statistical Inference for Generative Models with Maximum Mean Discrepancy François‐Xavier Briol Alessandro Barp Andrew B. Duncan Mark Girolami 27 70 0 13 Jun 2019
Topic Modeling via Full Dependence Mixtures D. Fisher Mark Kozdoba Shie Mannor 8 1 0 13 Jun 2019
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes R. Krishnan Mahesh Subedar Omesh Tickoo BDL 20 46 0 12 Jun 2019
Incremental Learning from Scratch for Task-Oriented Dialogue Systems Weikang Wang Jiajun Zhang Q. Li M. Hwang Chengqing Zong Zhifei Li CLL 28 21 0 12 Jun 2019
Learning Deep Generative Models with Annealed Importance Sampling Xinqiang Ding David J. Freedman VLM BDL GAN 28 10 0 12 Jun 2019
Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models Filipe Rodrigues Nicola Ortelli M. Bierlaire Francisco Câmara Pereira 17 17 0 10 Jun 2019
Sparse Variational Inference: Bayesian Coresets from Scratch Trevor Campbell Boyan Beronov 18 38 0 07 Jun 2019
Efficient non-conjugate Gaussian process factor models for spike count data using polynomial approximations Stephen L. Keeley D. Zoltowski Yiyi Yu Jacob L. Yates S. L. Smith Jonathan W. Pillow 23 20 0 07 Jun 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations Wu Lin Mohammad Emtiyaz Khan Mark Schmidt BDL 11 69 0 07 Jun 2019
An Introduction to Variational Autoencoders Diederik P. Kingma Max Welling BDL SSL DRL 33 2,295 0 06 Jun 2019
Can Graph Neural Networks Help Logic Reasoning? Yuyu Zhang Xinshi Chen Yu’an Yang Arun Ramamurthy Bo Li Yuan Qi Le Song NAI AI4CE 26 13 0 05 Jun 2019
Reliable training and estimation of variance networks N. Detlefsen Martin Jørgensen Søren Hauberg UQCV 19 86 0 04 Jun 2019
Universal Boosting Variational Inference Trevor Campbell Xinglong Li 13 30 0 04 Jun 2019
Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples Saeed Vahidian Baharan Mirzasoleiman A. Cloninger 26 0 0 03 Jun 2019
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems Geoffrey Roeder Paul K. Grant Andrew Phillips Neil Dalchau Edward Meeds 17 23 0 28 May 2019
Recursive Estimation for Sparse Gaussian Process Regression Manuel Schürch Dario Azzimonti A. Benavoli Marco Zaffalon 33 32 0 28 May 2019
Dirichlet Simplex Nest and Geometric Inference Mikhail Yurochkin Aritra Guha Yuekai Sun X. Nguyen 26 4 0 27 May 2019
A view of Estimation of Distribution Algorithms through the lens of Expectation-Maximization David H. Brookes A. Busia Clara Fannjiang Kevin Patrick Murphy Jennifer Listgarten 27 22 0 24 May 2019
Sequential Gaussian Processes for Online Learning of Nonstationary Functions M. Zhang Bianca Dumitrascu Sinead Williamson Barbara E. Engelhardt 28 8 0 24 May 2019
Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation Théo Galy-Fajou F. Wenzel Christian Donner Manfred Opper 33 29 0 23 May 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 34 37 0 23 May 2019
MaxEntropy Pursuit Variational Inference Evgenii Egorov Kirill Neklyudov R. Kostoev Evgeny Burnaev BDL 11 3 0 20 May 2019
Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling Hao Zhang Bo Chen Long Tian Zhengjue Wang Mingyuan Zhou DRL 32 6 0 18 May 2019
Stochastic Blockmodels meet Graph Neural Networks Nikhil Mehta Lawrence Carin Piyush Rai BDL 35 80 0 14 May 2019
A Contrastive Divergence for Combining Variational Inference and MCMC Francisco J. R. Ruiz Michalis K. Titsias BDL 19 60 0 10 May 2019
Random Function Priors for Correlation Modeling Aonan Zhang John Paisley 16 2 0 09 May 2019
Monte Carlo Co-Ordinate Ascent Variational Inference Lifeng Ye A. Beskos Maria de Iorio Jie Hao DRL BDL 11 1 0 09 May 2019
Variational Autoencoders for Sparse and Overdispersed Discrete Data He Zhao Piyush Rai Lan Du Wray Buntine Mingyuan Zhou DRL 13 1 0 02 May 2019
Semi-Conditional Normalizing Flows for Semi-Supervised Learning Andrei Atanov Alexandra Volokhova Arsenii Ashukha Ivan Sosnovik Dmitry Vetrov BDL 29 41 0 01 May 2019
Latent Variable Session-Based Recommendation D. Rohde Stephen Bonner BDL 22 3 0 24 Apr 2019
Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients Yu Chen Tom Diethe Neil D. Lawrence CLL BDL 14 13 0 24 Apr 2019
Latent Variable Algorithms for Multimodal Learning and Sensor Fusion Lijiang Guo DRL 24 1 0 23 Apr 2019
An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning Yaoyao Liu Bernt Schiele Qianru Sun BDL 40 128 0 17 Apr 2019
Copula-like Variational Inference Marcel Hirt P. Dellaportas Alain Durmus 12 5 0 15 Apr 2019
Variational Bayes for high-dimensional linear regression with sparse priors Kolyan Ray Botond Szabó 33 99 0 15 Apr 2019
A Generalization Bound for Online Variational Inference Badr-Eddine Chérief-Abdellatif Pierre Alquier Mohammad Emtiyaz Khan BDL 23 25 0 08 Apr 2019
Bayesian Non-Parametric Multi-Source Modelling Based Determined Blind Source Separation Chaitanya Narisetty Tatsuya Komatsu Reishi Kondo 14 3 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 12 31 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 21 9 0 05 Apr 2019
Minimum Volume Topic Modeling B. Jang Alfred Hero 24 4 0 03 Apr 2019
Generalized Variational Inference: Three arguments for deriving new Posteriors Jeremias Knoblauch Jack Jewson Theodoros Damoulas DRL BDL 39 105 0 03 Apr 2019