| 2024 | WWW | The Effect of Alter Ego Accounts on A/B Tests in Social Networks. | Katherine Avery, Amir Houmansadr, David D. Jensen |
| 2023 | WSC | Causal Dynamic Bayesian Networks for Simulation Metamodeling. | Pracheta Amaranath, Peter J. Haas, David D. Jensen, Sam Witty |
| 2021 | AAAI | Improving Causal Inference by Increasing Model Expressiveness. | David D. Jensen |
| 2021 | ICDCS | Preserving Privacy in Personalized Models for Distributed Mobile Services. | Akanksha Atrey, Prashant J. Shenoy, David D. Jensen |
| 2021 | ICML | How and Why to Use Experimental Data to Evaluate Methods for Observational Causal Inference. | Amanda Gentzel, Purva Pruthi, David D. Jensen |
| 2020 | ACL | Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates. | Katherine A. Keith, David D. Jensen, Brendan O'Connor |
| 2020 | ICLR | Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning. | Akanksha Atrey, Kaleigh Clary, David D. Jensen |
| 2020 | ICML | Causal Inference using Gaussian Processes with Structured Latent Confounders. | Sam Witty, Kenta Takatsu, David D. Jensen, Vikash Mansinghka |
| 2019 | UAI | Object Conditioning for Causal Inference. | David D. Jensen, Javier Burroni, Matthew J. Rattigan |
| 2019 | SDM | Identifying When Effect Restoration Will Improve Estimates of Causal Effect. | Hseyin Oktay, Akanksha Atrey, David D. Jensen |
| 2016 | KDD | Inferring Network Effects from Observational Data. | David T. Arbour, Dan Garant, David D. Jensen |
| 2016 | SIGIR | Controversy Detection in Wikipedia Using Collective Classification. | Shiri Dori-Hacohen, David D. Jensen, James Allan |
| 2016 | UAI | Inferring Causal Direction from Relational Data. | David T. Arbour, Katerina Marazopoulou, David D. Jensen |
| 2015 | AAAI | Learning to Uncover Deep Musical Structure. | Phillip B. Kirlin, David D. Jensen |
| 2015 | SIGCSE | Teaching Computing as Science in a Research Experience. | Jerod J. Weinman, David D. Jensen, David Lopatto |
| 2015 | UAI | Learning the Structure of Causal Models with Relational and Temporal Dependence. | Katerina Marazopoulou, Marc E. Maier, David D. Jensen |
| 2015 | UAI | Learning the Structure of Causal Models with Relational and Temporal Dependence. | Katerina Marazopoulou, Marc E. Maier, David D. Jensen |
| 2014 | FlAIRS | Strategy Mining. | Xiaoxi Xu, David D. Jensen, Edwina L. Rissland |
| 2014 | WWW | Online dating recommendations: matching markets and learning preferences. | Kun Tu, Bruno F. Ribeiro, David D. Jensen, Don Towsley, Benyuan Liu, Hua Jiang, Xiaodong Wang |
| 2014 | UAI | Propensity Score Matching for Causal Inference with Relational Data. | David T. Arbour, Katerina Marazopoulou, Dan Garant, David D. Jensen |
| 2014 | SDM | Classifier-Adjusted Density Estimation for Anomaly Detection and One-Class Classification. | Lisa Friedland, Amanda Gentzel, David D. Jensen |
| 2013 | ICML | Copy or Coincidence? A Model for Detecting Social Influence and Duplication Events. | Lisa Friedland, David D. Jensen, Michael Lavine |
| 2013 | KDD | Detecting insider threats in a real corporate database of computer usage activity. | Ted E. Senator, Henry G. Goldberg, Alex Memory, William T. Young, Brad Rees, Robert Pierce, Daniel Huang, Matthew Reardon, David A. Bader, Edmond Chow, Irfan A. Essa, Joshua Jones, Vinay Bettadapura, Duen Horng Chau, Oded Green, Oguz Kaya, Anita Zakrzewska, Erica Briscoe, Rudolph L. Mappus IV, Robert McColl, Lora Weiss, Thomas G. Dietterich, Alan Fern, Weng-Keen Wong, Shubhomoy Das, Andrew Emmott, Jed Irvine, Jay Yoon Lee, Danai Koutra, Christos Faloutsos, Daniel D. Corkill, Lisa Friedland, Amanda Gentzel, David D. Jensen |
| 2013 | UAI | A Sound and Complete Algorithm for Learning Causal Models from Relational Data. | Marc E. Maier, Katerina Marazopoulou, David T. Arbour, David D. Jensen |
| 2011 | AAAI | Relational Blocking for Causal Discovery. | Matthew J. Rattigan, Marc E. Maier, David D. Jensen |
| 2010 | AAAI | Learning Causal Models of Relational Domains. | Marc E. Maier, Brian J. Taylor, Hseyin Oktay, David D. Jensen |
| 2010 | ICDM | Leveraging D-Separation for Relational Data Sets. | Matthew J. Rattigan, David D. Jensen |
| 2010 | KDD | Causal discovery in social media using quasi-experimental designs. | Hseyin Oktay, Brian J. Taylor, David D. Jensen |
| 2010 | SDM | The Application of Statistical Relational Learning to a Database of Criminal and Terrorist Activity. | Brian Delaney, Andrew S. Fast, William M. Campbell, Clifford J. Weinstein, David D. Jensen |
| 2009 | IC3K | Knowledge Discovery by Design. | David D. Jensen |
| 2009 | ICDM | Accurate Estimation of the Degree Distribution of Private Networks. | Michael Hay, Chao Li, Gerome Miklau, David D. Jensen |
| 2008 | ICDM | Why Stacked Models Perform Effective Collective Classification. | Andrew S. Fast, David D. Jensen |
| 2008 | KDD | Automatic identification of quasi-experimental designs for discovering causal knowledge. | David D. Jensen, Andrew S. Fast, Brian J. Taylor, Marc E. Maier |
| 2008 | KDD | Social networks: looking ahead. | Ravi Kumar, Alexander Tuzhilin, Christos Faloutsos, David D. Jensen, Gueorgi Kossinets, Jure Leskovec, Andrew Tomkins |
| 2007 | ICDM | Exploiting Network Structure for Active Inference in Collective Classification. | Matthew J. Rattigan, Marc E. Maier, David D. Jensen, Bin Wu, Xin Pei, Jianbin Tan, Yi Wang |
| 2007 | ICML | Graph clustering with network structure indices. | Matthew J. Rattigan, Marc E. Maier, David D. Jensen |
| 2007 | ILP | Beyond Prediction: Directions for Probabilistic and Relational Learning. | David D. Jensen |
| 2007 | ILP | Bias/Variance Analysis for Relational Domains. | Jennifer Neville, David D. Jensen |
| 2007 | KDD | Relational data pre-processing techniques for improved securities fraud detection. | Andrew S. Fast, Lisa Friedland, Marc E. Maier, Brian J. Taylor, David D. Jensen, Henry G. Goldberg, John Komoroske |
| 2007 | KDD | Finding tribes: identifying close-knit individuals from employment patterns. | Lisa Friedland, David D. Jensen |
| 2007 | SIGIR | Recommending citations for academic papers. | Trevor Strohman, W. Bruce Croft, David D. Jensen |
| 2006 | CIKM | Representing documents with named entities for story link detection (SLD). | Chirag Shah, W. Bruce Croft, David D. Jensen |
| 2006 | INFOCOM | MaxProp: Routing for Vehicle-Based Disruption-Tolerant Networks. | John Burgess, Brian Gallagher, David D. Jensen, Brian Neil Levine |
| 2006 | KDD | Using structure indices for efficient approximation of network properties. | Matthew J. Rattigan, Marc E. Maier, David D. Jensen |
| 2005 | AAAI | A Relational Representation for Procedural Task Knowledge. | Stephen Hart, Roderic A. Grupen, David D. Jensen |
| 2005 | ICDM | Leveraging Relational Autocorrelation with Latent Group Models. | Jennifer Neville, David D. Jensen |
| 2005 | IJCAI | Decentralized Search in Networks Using Homophily and Degree Disparity. | zgr Simsek, David D. Jensen |
| 2005 | KDD | Creating social networks to improve peer-to-peer networking. | Andrew S. Fast, David D. Jensen, Brian Neil Levine |
| 2005 | KDD | Using relational knowledge discovery to prevent securities fraud. | Jennifer Neville, zgr Simsek, David D. Jensen, John Komoroske, Kelly Palmer, Henry G. Goldberg |
| 2004 | ICDM | Dependency Networks for Relational Data. | Jennifer Neville, David D. Jensen |
| 2004 | KDD | Why collective inference improves relational classification. | David D. Jensen, Jennifer Neville, Brian Gallagher |
| 2003 | ICDM | Simple Estimators for Relational Bayesian Classifiers. | Jennifer Neville, David D. Jensen, Brian Gallagher |
| 2003 | ICML | Avoiding Bias when Aggregating Relational Data with Degree Disparity. | David D. Jensen, Jennifer Neville, Michael Hay |
| 2003 | ICML | Identifying Predictive Structures in Relational Data Using Multiple Instance Learning. | Amy McGovern, David D. Jensen |
| 2003 | KDD | Information awareness: a prospective technical assessment. | David D. Jensen, Matthew J. Rattigan, Hannah Blau |
| 2003 | KDD | Learning relational probability trees. | Jennifer Neville, David D. Jensen, Lisa Friedland, Michael Hay |
| 2002 | ICML | Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning. | David D. Jensen, Jennifer Neville |
| 2002 | ILP | Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners. | David D. Jensen, Jennifer Neville |
| 2000 | CIKM | Language Models for Financial News Recommendation. | Victor Lavrenko, Matthew D. Schmill, Dawn J. Lawrie, Paul Ogilvie, David D. Jensen, James Allan |
| 2000 | GD | Knowledge Discovery from Graphs (Invited Talk). | David D. Jensen |
| 1999 | AAAI | Learning Quantitative Knowledge for Multiagent Coordination. | David D. Jensen, Michael Atighetchi, Rgis Vincent, Victor R. Lesser |
| 1999 | AAAI | Toward a Theoretical Understanding of Why and When Decision Tree Pruning Algorithms Fail. | Tim Oates, David D. Jensen |
| 1999 | AISTATS | Statistical challenges to inductive inference in linked data. | David D. Jensen |
| 1999 | KDD | Efficient Progressive Sampling. | Foster J. Provost, David D. Jensen, Tim Oates |
| 1998 | KDD | Large Datasets Lead to Overly Complex Models: An Explanation and a Solution. | Tim Oates, David D. Jensen |
| 1997 | AISTATS | The Effects of Training Set Size on Decision Tree Complexity. | Tim Oates, David D. Jensen |
| 1997 | AISTATS | A Family of Algorithms for Finding Temporal Structure in Data. | Tim Oates, Matthew D. Schmill, David D. Jensen, Paul R. Cohen |
| 1997 | AISTATS | Overfitting Explained. | Paul R. Cohen, David D. Jensen |
| 1997 | AISTATS | Adjusting for Multiple Testing in Decision Tree Pruning. | David D. Jensen |
| 1997 | ICML | The Effects of Training Set Size on Decision Tree Complexity. | Tim Oates, David D. Jensen |
| 1997 | IDA | Building Simple Models: A Case Study with Decision Trees. | David D. Jensen, Tim Oates, Paul R. Cohen |
| 1997 | KDD | Adjusting for Multiple Comparisons in Decision Tree Pruning. | David D. Jensen, Matthew D. Schmill |
| 1996 | ISTAS | Technology, language, and public decisions: finding common ground for experts and citizens. | David D. Jensen, Todd M. La Porte |