Jensen, David

13 publications

CLeaR 2025 Compositional Models for Estimating Causal Effects Purva Pruthi, David Jensen

NeurIPSW 2022 Improving the Efficiency of the PC Algorithm by Using Model-Based Conditional Independence Tests Erica Cai, Andrew McGregor, David Jensen

ICML 2021 How and Why to Use Experimental Data to Evaluate Methods for Observational Causal Inference Amanda M Gentzel, Purva Pruthi, David Jensen

ICML 2020 Causal Inference Using Gaussian Processes with Structured Latent Confounders Sam Witty, Kenta Takatsu, David Jensen, Vikash Mansinghka

ICLR 2020 Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning Akanksha Atrey, Kaleigh Clary, David Jensen

UAI 2019 Object Conditioning for Causal Inference David Jensen, Javier Burroni, Matthew Rattigan

NeurIPS 2019 The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data Amanda Gentzel, Dan Garant, David Jensen

ICML 2013 Copy or Coincidence? a Model for Detecting Social Influence and Duplication Events Lisa Friedland, David Jensen, Michael Lavine

JMLR 2007 Relational Dependency Networks Jennifer Neville, David Jensen

AISTATS 1997 A Family of Algorithms for Finding Temporal Structure in Data Tim Oates, Matthew J. Schmill, David Jensen, Paul R. Cohen

AISTATS 1997 Adjusting for Multiple Testing in Decision Tree Pruning David Jensen

AISTATS 1997 Overfitting Explained Paul R. Cohen, David Jensen

AISTATS 1997 The Effects of Training Set Size on Decision Tree Complexity Tim Oates, David Jensen