David M. Blei

According to our database1, David M. Blei authored at least 190 papers between 2001 and 2018.

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Awards

ACM Fellow

ACM Fellow 2015, "For contributions to the theory and practice of probabilistic topic modeling and Bayesian machine learning.".

Timeline

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Bibliography

2018
A probabilistic approach to discovering dynamic full-brain functional connectivity patterns.
NeuroImage, 2018

The Deconfounded Recommender: A Causal Inference Approach to Recommendation.
CoRR, 2018

Avoiding Latent Variable Collapse With Generative Skip Models.
CoRR, 2018

Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data.
CoRR, 2018

Black Box FDR.
CoRR, 2018

The Blessings of Multiple Causes.
CoRR, 2018

Noisin: Unbiased Regularization for Recurrent Neural Networks.
CoRR, 2018

Equation Embeddings.
CoRR, 2018

Augment and Reduce: Stochastic Inference for Large Categorical Distributions.
CoRR, 2018

Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data.
CoRR, 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

SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements.
CoRR, 2017

Implicit Causal Models for Genome-wide Association Studies.
CoRR, 2017

Structured Embedding Models for Grouped Data.
CoRR, 2017

Frequentist Consistency of Variational Bayes.
CoRR, 2017

Deep and Hierarchical Implicit Models.
CoRR, 2017

Deep Probabilistic Programming.
CoRR, 2017

Dynamic Bernoulli Embeddings for Language Evolution.
CoRR, 2017

Stochastic Gradient Descent as Approximate Bayesian Inference.
CoRR, 2017

Proximity Variational Inference.
CoRR, 2017

Hierarchical Implicit Models and Likelihood-Free 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

Zero-Inflated 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 Acceptance-Rejection 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
Reweighted Data for Robust Probabilistic Models.
CoRR, 2016

Edward: A library for probabilistic modeling, inference, and criticism.
CoRR, 2016

Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations.
CoRR, 2016

Exponential Family Embeddings.
CoRR, 2016

Deep Survival Analysis.
CoRR, 2016

Operator Variational Inference.
CoRR, 2016

A Variational Analysis of Stochastic Gradient Algorithms.
CoRR, 2016

Automatic Differentiation Variational Inference.
CoRR, 2016

Posterior Dispersion Indices.
CoRR, 2016

The $χ$-Divergence for Approximate Inference.
CoRR, 2016

Variational Inference: A Review for Statisticians.
CoRR, 2016

Objective Variables for Probabilistic Revenue Maximization in Second-Price 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 Black-Box Variational Inference.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence.
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 Super-Resolution.
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

Variational Gaussian Process.
CoRR, 2015

Variational inference with copula augmentation.
CoRR, 2015

Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts.
CoRR, 2015

Objective Variables for Probabilistic Revenue Maximization in Second-Price Auctions with Reserve.
CoRR, 2015

Hierarchical Variational Models.
CoRR, 2015

Modeling User Exposure in Recommendation.
CoRR, 2015

Dynamic Poisson Factorization.
CoRR, 2015

The Survival Filter: Joint Survival Analysis with a Latent Time Series.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Population Empirical Bayes.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Scalable Recommendation with Hierarchical Poisson Factorization.
Proceedings of the Thirty-First 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

Deep Exponential Families.
CoRR, 2014

Black Box Variational Inference.
CoRR, 2014

Smoothed Gradients for Stochastic Variational Inference.
CoRR, 2014

Profile Predictive Inference.
CoRR, 2014

Deterministic Annealing for Stochastic Variational Inference.
CoRR, 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

Content-based 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

Learning with Scope, with Application to Information Extraction and Classification
CoRR, 2013

Scalable Recommendation with Poisson Factorization.
CoRR, 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 5-8, 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 5-8, 2013

An Adaptive Learning Rate for Stochastic Variational Inference.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Stick-Breaking Beta Processes and the Poisson Process.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Nested Hierarchical Dirichlet Processes
CoRR, 2012

The Issue-Adjusted Ideal Point Model
CoRR, 2012

A Bayesian Nonparametric Approach to Image Super-resolution
CoRR, 2012

Nonparametric Bayes Pachinko Allocation
CoRR, 2012

Nonparametric variational inference
CoRR, 2012

Continuous Time Dynamic Topic Models
CoRR, 2012

Multilingual Topic Models for Unaligned Text
CoRR, 2012

A Split-Merge MCMC Algorithm for the Hierarchical Dirichlet Process
CoRR, 2012

Stochastic Variational Inference.
CoRR, 2012

Probabilistic topic models.
Commun. ACM, 2012

Truncation-free 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 3-6, 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 3-6, 2012

How They Vote: Issue-Adjusted 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 3-6, 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 Mixed-Membership Modeling.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Dirichlet Process Mixtures of Generalized Linear Models.
Journal of Machine Learning Research, 2011

Distance Dependent Chinese Restaurant Processes.
Journal of Machine Learning Research, 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 12-14 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 Stick-Breaking 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

Syntactic Topic Models
CoRR, 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 6-9 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 6-9 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 (ICML-10), 2010

Bayesian Nonparametric Matrix Factorization for Recorded Music.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

A Language-based Approach to Measuring Scholarly Impact.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Distance dependent Chinese restaurant processes.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Building and using a semantivisual image hierarchy.
Proceedings of the Twenty-Third 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 7-10 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 7-10 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 7-10 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 7-10 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
Mixed Membership Stochastic Blockmodels.
Journal of Machine Learning Research, 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

Content-Based Musical Similarity Computation using the Hierarchical Dirichlet Process.
Proceedings of the ISMIR 2008, 2008

Data-Driven Recomposition using the Hierarchical Dirichlet Process Hidden Markov Model.
Proceedings of the 2008 International Computer Music Conference, 2008

2007
Mixed membership stochastic blockmodels.
CoRR, 2007

Nonparametric Bayes Pachinko Allocation.
Proceedings of the UAI 2007, 2007

PU-BCD: Exponential Family Models for the Coarse- and Fine-Grained All-Words 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 EMNLP-CoNLL 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
Latent Dirichlet Allocation.
Journal of Machine Learning Research, 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


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