David M. Blei
According to our database^{1},
David M. Blei
authored at least 132 papers
between 2001 and 2018.
Collaborative distances:
Collaborative distances:
Awards
ACM Fellow
ACM Fellow 2015, "For contributions to the theory and practice of probabilistic topic modeling and Bayesian machine learning.".
Timeline
Legend:
Book In proceedings Article PhD thesis OtherLinks
Homepages:

at zbmath.org

at www.acm.org

at id.loc.gov

at dl.acm.org
On csauthors.net:
Bibliography
2018
A probabilistic approach to discovering dynamic fullbrain functional connectivity patterns.
NeuroImage, 2018
Technical perspective: Expressive probabilistic models and scalable method of moments.
Commun. ACM, 2018
Dynamic Embeddings for Language Evolution.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018
Black Box FDR.
Proceedings of the 35th International Conference on Machine Learning, 2018
Augment and Reduce: Stochastic Inference for Large Categorical Distributions.
Proceedings of the 35th International Conference on Machine Learning, 2018
Noisin: Unbiased Regularization for Recurrent Neural Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018
Variational Sequential Monte Carlo.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proximity Variational Inference.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Stochastic Gradient Descent as Approximate Bayesian Inference.
Journal of Machine Learning Research, 2017
Automatic Differentiation Variational Inference.
Journal of Machine Learning Research, 2017
Hierarchical Implicit Models and LikelihoodFree Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Structured Embedding Models for Grouped Data.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Context Selection for Embedding Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Variational Inference via \chi Upper Bound Minimization.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Robust Probabilistic Modeling with Bayesian Data Reweighting.
Proceedings of the 34th International Conference on Machine Learning, 2017
ZeroInflated Exponential Family Embeddings.
Proceedings of the 34th International Conference on Machine Learning, 2017
Evaluating Bayesian Models with Posterior Dispersion Indices.
Proceedings of the 34th International Conference on Machine Learning, 2017
Reparameterization Gradients through AcceptanceRejection Sampling Algorithms.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Objective Variables for Probabilistic Revenue Maximization in SecondPrice Auctions with Reserve.
Proceedings of the 25th International Conference on World Wide Web, 2016
Modeling User Exposure in Recommendation.
Proceedings of the 25th International Conference on World Wide Web, 2016
Overdispersed BlackBox Variational Inference.
Proceedings of the ThirtySecond Conference on Uncertainty in Artificial Intelligence, 2016
Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Cooccurrence.
Proceedings of the 10th ACM Conference on Recommender Systems, 2016
The Generalized Reparameterization Gradient.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Exponential Family Embeddings.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Operator Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Deep Survival Analysis.
Proceedings of the 1st Machine Learning in Health Care, 2016
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Hierarchical Variational Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016
A Variational Analysis of Stochastic Gradient Algorithms.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Detecting and Characterizing Events.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016
Variational Tempering.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
2015
A Bayesian Nonparametric Approach to Image SuperResolution.
IEEE Trans. Pattern Anal. Mach. Intell., 2015
Nested Hierarchical Dirichlet Processes.
IEEE Trans. Pattern Anal. Mach. Intell., 2015
Distance Dependent Infinite Latent Feature Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2015
Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis.
JAMIA, 2015
The Survival Filter: Joint Survival Analysis with a Latent Time Series.
Proceedings of the ThirtyFirst Conference on Uncertainty in Artificial Intelligence, 2015
Population Empirical Bayes.
Proceedings of the ThirtyFirst Conference on Uncertainty in Artificial Intelligence, 2015
Scalable Recommendation with Hierarchical Poisson Factorization.
Proceedings of the ThirtyFirst Conference on Uncertainty in Artificial Intelligence, 2015
Dynamic Poisson Factorization.
Proceedings of the 9th ACM Conference on Recommender Systems, 2015
A Probabilistic Model for Using Social Networks in Personalized Item Recommendation.
Proceedings of the 9th ACM Conference on Recommender Systems, 2015
Copula variational inference.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
The Population Posterior and Bayesian Modeling on Streams.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Automatic Variational Inference in Stan.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015
Deep Exponential Families.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015
Stochastic Structured Variational Inference.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015
2014
Bayesian Nonnegative Matrix Factorization with Stochastic Variational Inference.
Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014
Introduction to Mixed Membership Models and Methods.
Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014
Decomposing spatiotemporal brain patterns into topographic latent sources.
NeuroImage, 2014
Hierarchical topographic factor analysis.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014
Smoothed Gradients for Stochastic Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
A Filtering Approach to Stochastic Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Contentbased recommendations with Poisson factorization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
The Inverse Regression Topic Model.
Proceedings of the 31th International Conference on Machine Learning, 2014
Black Box Variational Inference.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014
Bayesian Nonparametric Poisson Factorization for Recommendation Systems.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014
2013
Deep Learning with Hierarchical Convolutional Factor Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2013
Variational inference in nonconjugate models.
Journal of Machine Learning Research, 2013
Stochastic variational inference.
Journal of Machine Learning Research, 2013
Efficient Online Inference for Bayesian Nonparametric Relational Models.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 58, 2013
Modeling Overlapping Communities with Node Popularities.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 58, 2013
An Adaptive Learning Rate for Stochastic Variational Inference.
Proceedings of the 30th International Conference on Machine Learning, 2013
2012
StickBreaking Beta Processes and the Poisson Process.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Probabilistic topic models.
Commun. ACM, 2012
Truncationfree Online Variational Inference for Bayesian Nonparametric Models.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
Scalable Inference of Overlapping Communities.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
How They Vote: IssueAdjusted Models of Legislative Behavior.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
Visualizing Topic Models.
Proceedings of the Sixth International Conference on Weblogs and Social Media, 2012
Variational Bayesian Inference with Stochastic Search.
Proceedings of the 29th International Conference on Machine Learning, 2012
Sparse stochastic inference for latent Dirichlet allocation.
Proceedings of the 29th International Conference on Machine Learning, 2012
Nonparametric variational inference.
Proceedings of the 29th International Conference on Machine Learning, 2012
2011
A topographic latent source model for fMRI data.
NeuroImage, 2011
Online Variational Inference for the Hierarchical Dirichlet Process.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011
The Discrete Infinite Logistic Normal Distribution for MixedMembership Modeling.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011
Spatial distance dependent Chinese restaurant processes for image segmentation.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 1214 December 2011, 2011
Collaborative topic modeling for recommending scientific articles.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011
Variational Inference for StickBreaking Beta Process Priors.
Proceedings of the 28th International Conference on Machine Learning, 2011
Predicting Legislative Roll Calls from Text.
Proceedings of the 28th International Conference on Machine Learning, 2011
Bayesian Checking for Topic Models.
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, 2011
2010
Probabilistic Topic Models.
IEEE Signal Process. Mag., 2010
Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
Dirichlet Process Mixtures of Generalized Linear Models.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies.
J. ACM, 2010
Online Learning for Latent Dirichlet Allocation.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 69 December 2010, 2010
Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 69 December 2010, 2010
Variational Inference for Adaptor Grammars.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2010
The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling.
Proceedings of the 27th International Conference on Machine Learning (ICML10), 2010
Bayesian Nonparametric Matrix Factorization for Recorded Music.
Proceedings of the 27th International Conference on Machine Learning (ICML10), 2010
A Languagebased Approach to Measuring Scholarly Impact.
Proceedings of the 27th International Conference on Machine Learning (ICML10), 2010
Distance dependent Chinese restaurant processes.
Proceedings of the 27th International Conference on Machine Learning (ICML10), 2010
Building and using a semantivisual image hierarchy.
Proceedings of the TwentyThird IEEE Conference on Computer Vision and Pattern Recognition, 2010
2009
Markov Topic Models.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009
Relational Topic Models for Document Networks.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009
Multilingual Topic Models for Unaligned Text.
Proceedings of the UAI 2009, 2009
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 710 December 2009, 2009
Variational Inference for the Nested Chinese Restaurant Process.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 710 December 2009, 2009
A Bayesian Analysis of Dynamics in Free Recall.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 710 December 2009, 2009
Reading Tea Leaves: How Humans Interpret Topic Models.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 710 December 2009, 2009
Connections between the lines: augmenting social networks with text.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009
Easy As CBA: A Simple Probabilistic Model for Tagging Music.
Proceedings of the 10th International Society for Music Information Retrieval Conference, 2009
Bayesian Spectral Matching: Turning Young MC into MC Hammer via MCMC Sampling.
Proceedings of the 2009 International Computer Music Conference, 2009
Simultaneous image classification and annotation.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009
2008
Continuous Time Dynamic Topic Models.
Proceedings of the UAI 2008, 2008
Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Syntactic Topic Models.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Mixed Membership Stochastic Blockmodels.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
ContentBased Musical Similarity Computation using the Hierarchical Dirichlet Process.
Proceedings of the ISMIR 2008, 2008
DataDriven Recomposition using the Hierarchical Dirichlet Process Hidden Markov Model.
Proceedings of the 2008 International Computer Music Conference, 2008
2007
Nonparametric Bayes Pachinko Allocation.
Proceedings of the UAI 2007, 2007
PUBCD: Exponential Family Models for the Coarse and FineGrained AllWords Tasks.
Proceedings of the 4th International Workshop on Semantic Evaluations, 2007
PUTOP: Turning Predominant Senses into a Topic Model for Word Sense Disambiguation.
Proceedings of the 4th International Workshop on Semantic Evaluations, 2007
Supervised Topic Models.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Hierarchical maximum entropy density estimation.
Proceedings of the Machine Learning, 2007
A Computational Approach to Style in American Poetry.
Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007
A Topic Model for Word Sense Disambiguation.
Proceedings of the EMNLPCoNLL 2007, 2007
2006
Nonparametric empirical Bayes for the Dirichlet process mixture model.
Statistics and Computing, 2006
Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span.
BMC Bioinformatics, 2006
Dynamic topic models.
Proceedings of the Machine Learning, 2006
Panel Discussion.
Proceedings of the Statistical Network Analysis: Models, Issues, and New Directions, 2006
Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysis.
Proceedings of the Statistical Network Analysis: Models, Issues, and New Directions, 2006
2005
Correlated Topic Models.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
A latent mixed membership model for relational data.
Proceedings of the 3rd international workshop on Link discovery, 2005
2004
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004
Integrating Topics and Syntax.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004
Variational methods for the Dirichlet process.
Proceedings of the Machine Learning, 2004
2003
Matching Words and Pictures.
Journal of Machine Learning Research, 2003
Modeling annotated data.
Proceedings of the SIGIR 2003: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, July 28, 2003
Hierarchical Topic Models and the Nested Chinese Restaurant Process.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003
2002
Learning with Scope, with Application to Information Extraction and Classification.
Proceedings of the UAI '02, 2002
2001
Topic Segmentation with an Aspect Hidden Markov Model.
Proceedings of the SIGIR 2001: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2001
Latent Dirichlet Allocation.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001