| 2025 | ICLR | ELBOing Stein: Variational Bayes with Stein Mixture Inference. | Ola Rnning, Eric T. Nalisnick, Christophe Ley, Padhraic Smyth, Thomas Hamelryck |
| 2025 | ICML | Bayesian Inference for Correlated Human Experts and Classifiers. | Markelle Kelly, Alex James Boyd, Samuel Showalter, Mark Steyvers, Padhraic Smyth |
| 2024 | AISTATS | Probabilistic Modeling for Sequences of Sets in Continuous-Time. | Yuxin Chang, Alex J. Boyd, Padhraic Smyth |
| 2024 | AISTATS | Functional Flow Matching. | Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth |
| 2024 | AISTATS | Bayesian Online Learning for Consensus Prediction. | Samuel Showalter, Alex J. Boyd, Padhraic Smyth, Mark Steyvers |
| 2024 | EMNLP | Perceptions of Linguistic Uncertainty by Language Models and Humans. | Catarina G. Belm, Markelle Kelly, Mark Steyvers, Sameer Singh, Padhraic Smyth |
| 2023 | AAAI | Variable-Based Calibration for Machine Learning Classifiers. | Markelle Kelly, Padhraic Smyth |
| 2023 | AISTATS | Probabilistic Querying of Continuous-Time Event Sequences. | Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth |
| 2023 | AISTATS | Diffusion Generative Models in Infinite Dimensions. | Gavin Kerrigan, Justin Ley, Padhraic Smyth |
| 2023 | ICML | Deep Anomaly Detection under Labeling Budget Constraints. | Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph |
| 2023 | UAI | Inference for mark-censored temporal point processes. | Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth |
| 2022 | ICML | Fair Generalized Linear Models with a Convex Penalty. | Hyungrok Do, Preston Putzel, Axel S. Martin, Padhraic Smyth, Judy Zhong |
| 2021 | AAAI | Active Bayesian Assessment of Black-Box Classifiers. | Disi Ji, Robert L. Logan IV, Padhraic Smyth, Mark Steyvers |
| 2019 | ICML | Dropout as a Structured Shrinkage Prior. | Eric T. Nalisnick, Jos Miguel Hernndez-Lobato, Padhraic Smyth |
| 2018 | AISTATS | Learning Priors for Invariance. | Eric T. Nalisnick, Padhraic Smyth |
| 2018 | EDM | Understanding Student Procrastination via Mixture Models. | Jihyun Park, Renzhe Yu, Fernando Rodriguez, Rachel B. Baker, Padhraic Smyth, Mark Warschauer |
| 2018 | WWW | Prediction of Sparse User-Item Consumption Rates with Zero-Inflated Poisson Regression. | Moshe Lichman, Padhraic Smyth |
| 2017 | ICLR | Stick-Breaking Variational Autoencoders. | Eric T. Nalisnick, Padhraic Smyth |
| 2017 | ICLR | Variational Reference Priors. | Eric T. Nalisnick, Padhraic Smyth |
| 2017 | LAK | Detecting changes in student behavior from clickstream data. | Jihyun Park, Kameryn Denaro, Fernando Rodriguez, Padhraic Smyth, Mark Warschauer |
| 2017 | UAI | Learning Approximately Objective Priors. | Eric T. Nalisnick, Padhraic Smyth |
| 2016 | AAAI | Analyzing NIH Funding Patterns over Time with Statistical Text Analysis. | Jihyun Park, Margaret Blume-Kohout, Ralf Krestel, Eric T. Nalisnick, Padhraic Smyth |
| 2015 | ICWSM | Modeling Response Time in Digital Human Communication. | Nicholas Martin Navaroli, Padhraic Smyth |
| 2015 | KDD | From Group to Individual Labels Using Deep Features. | Dimitrios Kotzias, Misha Denil, Nando de Freitas, Padhraic Smyth |
| 2015 | NAACL | Recursive Neural Networks for Coding Therapist and Patient Behavior in Motivational Interviewing. | Michael Tanana, Kevin Hallgren, Zac E. Imel, David C. Atkins, Padhraic Smyth, Vivek Srikumar |
| 2014 | AISTATS | Approximate Slice Sampling for Bayesian Posterior Inference. | Christopher DuBois, Anoop Korattikara Balan, Max Welling, Padhraic Smyth |
| 2014 | KDD | Modeling human location data with mixtures of kernel densities. | Moshe Lichman, Padhraic Smyth |
| 2014 | UAI | Annealing Paths for the Evaluation of Topic Models. | James R. Foulds, Padhraic Smyth |
| 2013 | AISTATS | Stochastic blockmodeling of relational event dynamics. | Christopher DuBois, Carter T. Butts, Padhraic Smyth |
| 2013 | EMNLP | Modeling Scientific Impact with Topical Influence Regression. | James R. Foulds, Padhraic Smyth |
| 2013 | KDD | Text-based measures of document diversity. | Kevin Bache, David Newman, Padhraic Smyth |
| 2013 | KDD | Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation. | James R. Foulds, Levi Boyles, Christopher DuBois, Padhraic Smyth, Max Welling |
| 2013 | RecSys | Recommending patents based on latent topics. | Ralf Krestel, Padhraic Smyth |
| 2013 | SODA | Windows into Relational Events: Data Structures for Contiguous Subsequences of Edges. | Michael J. Bannister, Christopher DuBois, David Eppstein, Padhraic Smyth |
| 2011 | ICML | Dynamic Egocentric Models for Citation Networks. | Duy Quang Vu, Arthur U. Asuncion, David R. Hunter, Padhraic Smyth |
| 2011 | ICWSM | Latent Set Models for Two-Mode Network Data. | Christopher DuBois, James R. Foulds, Padhraic Smyth |
| 2011 | SDM | Multi-Instance Mixture Models. | James R. Foulds, Padhraic Smyth |
| 2010 | ICML | Particle Filtered MCMC-MLE with Connections to Contrastive Divergence. | Arthur U. Asuncion, Qiang Liu, Alexander T. Ihler, Padhraic Smyth |
| 2010 | KDD | Modeling relational events via latent classes. | Christopher DuBois, Padhraic Smyth |
| 2009 | UAI | On Smoothing and Inference for Topic Models. | Arthur U. Asuncion, Max Welling, Padhraic Smyth, Yee Whye Teh |
| 2008 | CIKM | Combining concept hierarchies and statistical topic models. | Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers |
| 2008 | KDD | Probabilistic Analysis of a Large-Scale Urban Traffic Sensor Data Set. | Jon Hutchins, Alexander Ihler, Padhraic Smyth |
| 2008 | KDD | Fast collapsed gibbs sampling for latent dirichlet allocation. | Ian Porteous, David Newman, Alexander Ihler, Arthur U. Asuncion, Padhraic Smyth, Max Welling |
| 2007 | ICML | Infinite mixtures of trees. | Sergey Kirshner, Padhraic Smyth |
| 2006 | ALT | Data-Driven Discovery Using Probabilistic Hidden Variable Models. | Padhraic Smyth |
| 2006 | DIS | Data-Driven Discovery Using Probabilistic Hidden Variable Models. | Padhraic Smyth |
| 2006 | ISI | Analyzing Entities and Topics in News Articles Using Statistical Topic Models. | David Newman, Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers |
| 2006 | KDD | Adaptive event detection with time-varying poisson processes. | Alexander Ihler, Jon Hutchins, Padhraic Smyth |
| 2006 | KDD | Statistical entity-topic models. | David Newman, Chaitanya Chemudugunta, Padhraic Smyth |
| 2006 | MICCAI | A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data. | Seyoung Kim, Padhraic Smyth, Hal S. Stern |
| 2006 | UAI | Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation. | Ian Porteous, Alexander T. Ihler, Padhraic Smyth, Max Welling |
| 2005 | KDD | EventRank: a framework for ranking time-varying networks. | Joshua O'Madadhain, Padhraic Smyth |
| 2005 | MICCAI | Parametric Response Surface Models for Analysis of Multi-site fMRI Data. | Seyoung Kim, Padhraic Smyth, Hal S. Stern, Jessica A. Turner |
| 2005 | SDM | A Spectral Clustering Approach To Finding Communities in Graph. | Scott White, Padhraic Smyth |
| 2004 | KDD | Probabilistic author-topic models for information discovery. | Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, Thomas Griffiths |
| 2004 | UAI | Modeling Waveform Shapes with Random E ects Segmental Hidden Markov Models. | Seyoung Kim, Padhraic Smyth, Stefan Luther |
| 2004 | UAI | Conditional Chow-Liu Tree Structures for Modeling Discrete-Valued Vector Time Series. | Sergey Kirshner, Padhraic Smyth, Andrew Robertson |
| 2004 | UAI | The Author-Topic Model for Authors and Documents. | Michal Rosen-Zvi, Thomas L. Griffiths, Mark Steyvers, Padhraic Smyth |
| 2003 | AISTATS | Curve Clustering with Random Effects Regression Mixtures. | Scott Gaffney, Padhraic Smyth |
| 2003 | AISTATS | Clustering Markov States into Equivalence Classes using SVD and Heuristic Search Algorithms. | Xianping Ge, Sridevi Parise, Padhraic Smyth |
| 2003 | ICML | Unsupervised Learning with Permuted Data. | Sergey Kirshner, Sridevi Parise, Padhraic Smyth |
| 2003 | KDD | Translation-invariant mixture models for curve clustering. | Darya Chudova, Scott Gaffney, Eric Mjolsness, Padhraic Smyth |
| 2003 | KDD | Algorithms for estimating relative importance in networks. | Scott White, Padhraic Smyth |
| 2003 | UAI | Probabilistic Models For Joint Clustering And Time-Warping Of Multidimensional Curves. | Darya Chudova, Scott Gaffney, Padhraic Smyth |
| 2003 | SDM | Approximate Query Answering by Model Averaging. | Dmitry Pavlov, Padhraic Smyth |
| 2002 | ICPR | Probabilistic Model-Based Detection of Bent-Double Radio Galaxies. | Sergey Kirshner, Igor V. Cadez, Padhraic Smyth, Chandrika Kamath, Erick Cant-Paz |
| 2002 | KDD | Pattern discovery in sequences under a Markov assumption. | Darya Chudova, Padhraic Smyth |
| 2001 | KDD | Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction. | Igor V. Cadez, Padhraic Smyth, Heikki Mannila |
| 2001 | KDD | Probabilistic query models for transaction data. | Dmitry Pavlov, Padhraic Smyth |
| 2000 | ICDE | Approximate Query Answering with Frequent Sets and Maximum Entropy. | Heikki Mannila, Padhraic Smyth |
| 2000 | KDD | A general probabilistic framework for clustering individuals and objects. | Igor V. Cadez, Scott Gaffney, Padhraic Smyth |
| 2000 | KDD | Visualization of navigation patterns on a Web site using model-based clustering. | Igor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White |
| 2000 | KDD | Deformable Markov model templates for time-series pattern matching. | Xianping Ge, Padhraic Smyth |
| 2000 | KDD | Towards scalable support vector machines using squashing. | Dmitry Pavlov, Darya Chudova, Padhraic Smyth |
| 2000 | UAI | Probabilistic Models for Query Approximation with Large Sparse Binary Data Sets. | Dmitry Pavlov, Heikki Mannila, Padhraic Smyth |
| 1999 | AISTATS | Joint probabilistic clustering of multivariate and sequential data. | Padhraic Smyth |
| 1999 | ICML | Hierarchical Models for Screening of Iron Deficiency Anemia. | Igor V. Cadez, Christine E. McLaren, Padhraic Smyth, Geoffrey J. McLachlan |
| 1999 | KDD | Trajectory Clustering with Mixtures of Regression Models. | Scott Gaffney, Padhraic Smyth |
| 1999 | KDD | Prediction with Local Patterns using Cross-Entropy. | Heikki Mannila, Dmitry Pavlov, Padhraic Smyth |
| 1999 | SIGIR | Discovering Chinese Words from Unsegmented Text (poster abstract). | Xianping Ge, Wanda Pratt, Padhraic Smyth |
| 1998 | KDD | Rule Discovery from Time Series. | Gautam Das, King-Ip Lin, Heikki Mannila, Gopal Renganathan, Padhraic Smyth |
| 1997 | AIME | Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods. | William Rodman Shankle, Subramani Mani, Michael J. Pazzani, Padhraic Smyth |
| 1997 | AISTATS | Preface. | David Madigan, Padhraic Smyth |
| 1997 | AISTATS | Cross-validated Likelihood for Model Selection in Unsupervised Learning. | Padhraic Smyth |
| 1997 | AMIA | Differential Diagnosis of Dementia: A Knowledge Discovery and Data Mining (KDD) Approach. | Subramani Mani, William Rodman Shankle, Michael J. Pazzani, Padhraic Smyth, Malcolm B. Dick |
| 1997 | KDD | A Probabilistic Approach to Fast Pattern Matching in Time Series Databases. | Eamonn J. Keogh, Padhraic Smyth |
| 1997 | KDD | Detecting Atmospheric Regimes Using Cross-Validated Clustering. | Padhraic Smyth, Michael Ghil, Kayo Ide, Joseph Roden, Andrew Fraser |
| 1997 | KDD | Anytime Exploratory Data Analysis for Massive Data Sets. | Padhraic Smyth, David H. Wolpert |
| 1996 | KDD | Knowledge Discovery and Data Mining: Towards a Unifying Framework. | Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth |
| 1996 | KDD | Clustering Using Monte Carlo Cross-Validation. | Padhraic Smyth |
| 1995 | ICML | Retrofitting Decision Tree Classifiers Using Kernel Density Estimation. | Padhraic Smyth, Alexander G. Gray, Usama M. Fayyad |
| 1994 | CVPR | Automating the hunt for volcanoes on Venus. | Michael C. Burl, Usama M. Fayyad, Pietro Perona, Padhraic Smyth |
| 1994 | ICIP | Automated Analysis of Radar Imagery of Venus: Handling Lack of Ground Truth. | Michael C. Burl, Usama M. Fayyad, Pietro Perona, Padhraic Smyth |
| 1994 | KDD | Knowledge Discovery in Large Image Databases: Dealing with Uncertainties in Ground Truth. | Padhraic Smyth, Michael C. Burl, Usama M. Fayyad, Pietro Perona |
| 1992 | ICML | Detecting Novel Classes with Applications to Fault Diagnosis. | Padhraic Smyth, Jeff Mellstrom |
| 1990 | ECAI | A Hybrid Rule-Based/Bayesian Classifier. | Padhraic Smyth, Rodney M. Goodman, Charles M. Higgins |
| 1989 | ICML | The Induction of Probabilistic Rule Sets - The Itrule Algorithm. | Rodney M. Goodman, Padhraic Smyth |
| 1988 | ECAI | Information-Theoretic Rule Induction. | Rodney M. Goodman, Padhraic Smyth |