Ilya Shpitser

According to our database, Ilya Shpitser authored at least 69 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

IEEE Transactions on Neural Networks and Learning Systems Special Issue on Causal Discovery and Causality-Inspired Machine Learning.

Kun Zhang, Ilya Shpitser, Sara Magliacane, Davide Bacciu, Fei Wu, Changshui Zhang, Peter Spirtes

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Zero Inflation as a Missing Data Problem: a Proxy-based Approach.

Trung Phung, Jaron J. R. Lee, Opeyemi Oladapo-Shittu, Eili Y. Klein, Ayse Pinar Gurses, Susan M. Hannum, Kimberly Weems, Jill A. Marsteller, Sara E. Cosgrove, Sara C. Keller, Ilya Shpitser

CoRR, 2024

Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach.

Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Searching for explanations: testing social scientific methods in synthetic ground-truthed worlds.

Aurora C. Schmidt, Christopher J. Cameron, Corey Lowman, Joshua Brulé, Amruta Deshpande, Seyyed A. Fatemi, Vladimir Barash, Ariel M. Greenberg, Cash J. Costello, Eli Sherman, Rohit Bhattacharya, Liz McQuillan, Alexander Perrone, Yanni Kouskoulas, Clay Fink, June Zhang, Ilya Shpitser, Michael W. Macy

Comput. Math. Organ. Theory, March, 2023

The Proximal ID Algorithm.

Ilya Shpitser, Zach Wood-Doughty, Eric J. Tchetgen Tchetgen

J. Mach. Learn. Res., 2023

Evaluation of Active Feature Acquisition Methods for Static Feature Settings.

Henrik von Kleist, Alireza Zamanian, Ilya Shpitser, Narges Ahmidi

CoRR, 2023

Evaluation of Active Feature Acquisition Methods for Time-varying Feature Settings.

Henrik von Kleist, Alireza Zamanian, Ilya Shpitser, Narges Ahmidi

CoRR, 2023

An Introduction to Causal Inference Methods for Observational Human-Robot Interaction Research.

Jaron J. R. Lee, Gopika Ajaykumar, Ilya Shpitser, Chien-Ming Huang

CoRR, 2023

When does the ID algorithm fail?

Ilya Shpitser

CoRR, 2023

Ananke: A Python Package For Causal Inference Using Graphical Models.

Jaron J. R. Lee, Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser

CoRR, 2023

The Lauritzen-Chen Likelihood For Graphical Models.

Ilya Shpitser

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables.

Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser

J. Mach. Learn. Res., 2022

Causal and counterfactual views of missing data models.

Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser, James M. Robins

CoRR, 2022

Semiparametric causal sufficient dimension reduction of multidimensional treatments.

Razieh Nabi, Todd McNutt, Ilya Shpitser

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Causal Discovery in Linear Latent Variable Models Subject to Measurement Error.

Yuqin Yang, AmirEmad Ghassami, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Optimal Training of Fair Predictive Models.

Razieh Nabi, Daniel Malinsky, Ilya Shpitser

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference.

AmirEmad Ghassami, Andrew Ying, Ilya Shpitser, Eric Tchetgen Tchetgen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Multivariate Counterfactual Systems and Causal Graphical Models.

Ilya Shpitser, Thomas S. Richardson, James M. Robins

Proceedings of the Probabilistic and Causal Inference: The Works of Judea Pearl, 2022

An Interventionist Approach to Mediation Analysis.

James M. Robins, Thomas S. Richardson, Ilya Shpitser

Proceedings of the Probabilistic and Causal Inference: The Works of Judea Pearl, 2022

2021

Robustness in Deep Learning for Computer Vision: Mind the gap?

Nathan Drenkow, Numair Sani, Ilya Shpitser, Mathias Unberath

CoRR, 2021

An Automated Approach to Causal Inference in Discrete Settings.

Guilherme Duarte, Noam Finkelstein, Dean Knox, Jonathan Mummolo, Ilya Shpitser

CoRR, 2021

Multiply Robust Causal Mediation Analysis with Continuous Treatments.

AmirEmad Ghassami, Numair Sani, Yizhen Xu, Ilya Shpitser

CoRR, 2021

Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals.

AmirEmad Ghassami, Andrew Ying, Ilya Shpitser, Eric Tchetgen Tchetgen

CoRR, 2021

Generating Synthetic Text Data to Evaluate Causal Inference Methods.

Zach Wood-Doughty, Ilya Shpitser, Mark Dredze

CoRR, 2021

Path dependent structural equation models.

Ranjani Srinivasan, Jaron J. R. Lee, Rohit Bhattacharya, Ilya Shpitser

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Entropic Inequality Constraints from e-separation Relations in Directed Acyclic Graphs with Hidden Variables.

Noam Finkelstein, Beata Zjawin, Elie Wolfe, Ilya Shpitser, Robert W. Spekkens

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Partial Identifiability in Discrete Data with Measurement Error.

Noam Finkelstein, Roy Adams, Suchi Saria, Ilya Shpitser

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Differentiable Causal Discovery Under Unmeasured Confounding.

Rohit Bhattacharya, Tushar Nagarajan, Daniel Malinsky, Ilya Shpitser

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Path Dependent Structural Equation Models.

Ranjani Srinivasan, Jaron J. R. Lee, Narges Ahmidi, Ilya Shpitser

CoRR, 2020

A Semiparametric Approach to Interpretable Machine Learning.

Numair Sani, Jaron J. R. Lee, Razieh Nabi, Ilya Shpitser

CoRR, 2020

Explaining The Behavior Of Black-Box Prediction Algorithms With Causal Learning.

Numair Sani, Daniel Malinsky, Ilya Shpitser

CoRR, 2020

Identification Methods With Arbitrary Interventional Distributions as Inputs.

Jaron J. R. Lee, Ilya Shpitser

CoRR, 2020

Identification and Estimation of Causal Effects Defined by Shift Interventions.

Numair Sani, Jaron J. R. Lee, Ilya Shpitser

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Deriving Bounds And Inequality Constraints Using Logical Relations Among Counterfactuals.

Noam Finkelstein, Ilya Shpitser

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Full Law Identification in Graphical Models of Missing Data: Completeness Results.

Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser

Proceedings of the 37th International Conference on Machine Learning, 2020

General Identification of Dynamic Treatment Regimes Under Interference.

Eli Sherman, David Arbour, Ilya Shpitser

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Conditionally-additive-noise Models for Structure Learning.

Daniel Chicharro, Stefano Panzeri, Ilya Shpitser

CoRR, 2019

Intervening on Network Ties.

Eli Sherman, Ilya Shpitser

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Identification In Missing Data Models Represented By Directed Acyclic Graphs.

Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser, James M. Robins

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Causal Inference Under Interference And Network Uncertainty.

Rohit Bhattacharya, Daniel Malinsky, Ilya Shpitser

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Learning Optimal Fair Policies.

Razieh Nabi, Daniel Malinsky, Ilya Shpitser

Proceedings of the 36th International Conference on Machine Learning, 2019

A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects.

Daniel Malinsky, Ilya Shpitser, Thomas S. Richardson

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Identification of Personalized Effects Associated With Causal Pathways.

Ilya Shpitser, Eli Sherman

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Acyclic Linear SEMs Obey the Nested Markov Property.

Ilya Shpitser, Robin J. Evans, Thomas S. Richardson

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Estimation of Personalized Effects Associated With Causal Pathways.

Razieh Nabi, Phyllis Kanki, Ilya Shpitser

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Structure Learning Under Missing Data.

Alexander Gain, Ilya Shpitser

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

Identification and Estimation of Causal Effects from Dependent Data.

Eli Sherman, Ilya Shpitser

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Challenges of Using Text Classifiers for Causal Inference.

Zach Wood-Doughty, Ilya Shpitser, Mark Dredze

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Fair Inference on Outcomes.

Razieh Nabi, Ilya Shpitser

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016

Consistent Estimation of Functions of Data Missing Non-Monotonically and Not at Random.

Ilya Shpitser

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Missing Data as a Causal and Probabilistic Problem.

Ilya Shpitser, Karthika Mohan, Judea Pearl

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Segregated Graphs and Marginals of Chain Graph Models.

Ilya Shpitser

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013

On the definition of a confounder

Tyler J. VanderWeele, Ilya Shpitser

CoRR, 2013

Counterfactual Graphical Models for Longitudinal Mediation Analysis With Unobserved Confounding.

Ilya Shpitser

Cogn. Sci., 2013

Sparse Nested Markov models with Log-linear Parameters.

Ilya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

2012

Nested Markov Properties for Acyclic Directed Mixed Graphs.

Thomas S. Richardson, James M. Robins, Ilya Shpitser

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011

An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models.

Ilya Shpitser, Thomas S. Richardson, James M. Robins

Proceedings of the UAI 2011, 2011

2010

Detecting the Presence and Absence of Causal Relationships between Expression of Yeast Genes with Very Few Samples.

Eun Yong Kang, Chun Ye, Ilya Shpitser, Eleazar Eskin

J. Comput. Biol., 2010

On the Validity of Covariate Adjustment for Estimating Causal Effects.

Ilya Shpitser, Tyler J. VanderWeele, James M. Robins

Proceedings of the UAI 2010, 2010

Respecting Markov Equivalence in Computing Posterior Probabilities of Causal Graphical Features.

Eun Yong Kang, Ilya Shpitser, Eleazar Eskin

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009

Effects of Treatment on the Treated: Identification and Generalization.

Ilya Shpitser, Judea Pearl

Proceedings of the UAI 2009, 2009

Testing Edges by Truncations.

Ilya Shpitser, Thomas S. Richardson, James M. Robins

Proceedings of the IJCAI 2009, 2009

2008

Complete Identification Methods for the Causal Hierarchy.

Ilya Shpitser, Judea Pearl

J. Mach. Learn. Res., 2008

Dormant Independence.

Ilya Shpitser, Judea Pearl

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007

What Counterfactuals Can Be Tested.

Ilya Shpitser, Judea Pearl

Proceedings of the UAI 2007, 2007

2006

Identification of Conditional Interventional Distributions.

Ilya Shpitser, Judea Pearl

Proceedings of the UAI '06, 2006

Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models.

Ilya Shpitser, Judea Pearl

Proceedings of the Proceedings, 2006

2005

Identifiability of Path-Specific Effects.

Chen Avin, Ilya Shpitser, Judea Pearl

Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

2002

Identity Uncertainty and Citation Matching.

Hanna Pasula, Bhaskara Marthi, Brian Milch, Stuart Russell, Ilya Shpitser

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002