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ORCIDJudea Pearl
Person information
- affiliation: University of California, Los Angeles, CA, USA
- award (2011): Turing Award
- award (2008): Benjamin Franklin Medal
- award (2003): ACM - AAAI Allen Newell Award
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2020 – today
- 2024
[c137]Ang Li, Judea Pearl:
Probabilities of Causation with Nonbinary Treatment and Effect. AAAI 2024: 20465-20472- [c136]Ang Li, Judea Pearl:
Unit Selection with Nonbinary Treatment and Effect. AAAI 2024: 20473-20480 - 2023
- [c135]Ang Li, Judea Pearl:
Probabilities of Causation: Role of Observational Data. AISTATS 2023: 10012-10027 - [c134]Chi Zhang, Karthika Mohan, Judea Pearl:
Causal Inference under Interference and Model Uncertainty. CLeaR 2023: 371-385 - [i61]Ang Li, Scott Mueller, Judea Pearl:
Epsilon-Identifiability of Causal Quantities. CoRR abs/2301.12022 (2023) - 2022
- [c133]Ang Li, Judea Pearl:
Unit Selection with Causal Diagram. AAAI 2022: 5765-5772 - [c132]Ang Li, Judea Pearl:
Bounds on Causal Effects and Application to High Dimensional Data. AAAI 2022: 5773-5780 - [c131]Scott Mueller, Ang Li, Judea Pearl:
Causes of Effects: Learning Individual Responses from Population Data. IJCAI 2022: 2712-2718 - [c130]Chi Zhang, Karthika Mohan, Judea Pearl:
Causal Inference with Non-IID Data using Linear Graphical Models. NeurIPS 2022 - [p23]Judea Pearl:
Turing Award Lecture. Probabilistic and Causal Inference 2022: 11-28 - [p22]Judea Pearl:
Heuristics - Introduction. Probabilistic and Causal Inference 2022: 57-60 - [p21]Judea Pearl:
Asymptotic Properties of Minimax Trees and Game-Searching Procedures. Probabilistic and Causal Inference 2022: 61-90 - [p20]Judea Pearl:
The Solution for the Branching Factor of the Alpha-Beta Pruning Algorithm and its Optimality. Probabilistic and Causal Inference 2022: 91-102 - [p19]Judea Pearl:
On the Discovery and Generation of Certain Heuristics. Probabilistic and Causal Inference 2022: 103-122 - [p18]Judea Pearl:
Probabilities - Introduction. Probabilistic and Causal Inference 2022: 123-128 - [p17]Judea Pearl:
Reverend Bayes on Inference Engines: A Distributed Hierarchical Approach. Probabilistic and Causal Inference 2022: 129-138 - [p16]Judea Pearl:
Fusion, Propagation, and Structuring in Belief Networks. Probabilistic and Causal Inference 2022: 139-188 - [p15]Judea Pearl, Azaria Paz:
GRAPHOIDS: Graph-Based Logic for Reasoning about Relevance Relations OrWhen Would x Tell You More about y If You Already Know z? Probabilistic and Causal Inference 2022: 189-200 - [p14]Judea Pearl:
System Z: A Natural Ordering of Defaults with Tractable Applications to Nonmonotonic Reasoning. Probabilistic and Causal Inference 2022: 201-214 - [p13]Judea Pearl:
Causality 1988-2001 - Introduction. Probabilistic and Causal Inference 2022: 215-220 - [p12]Thomas Verma, Judea Pearl:
Equivalence and Synthesis of Causal Models. Probabilistic and Causal Inference 2022: 221-236 - [p11]Alexander Balke, Judea Pearl:
Probabilistic Evaluation of Counterfactual Queries. Probabilistic and Causal Inference 2022: 237-254 - [p10]Judea Pearl:
Causal Diagrams for Empirical Research (With Discussions). Probabilistic and Causal Inference 2022: 255-316 - [p9]Judea Pearl:
Probabilities of Causation: Three Counterfactual Interpretations and Their Identification. Probabilistic and Causal Inference 2022: 317-372 - [p8]Judea Pearl:
Direct and Indirect Effects. Probabilistic and Causal Inference 2022: 373-392 - [p7]Judea Pearl:
Causality 2002-2020 - Introduction. Probabilistic and Causal Inference 2022: 393-398 - [p6]Judea Pearl:
Comment: Understanding Simpson's Paradox. Probabilistic and Causal Inference 2022: 399-412 - [p5]Karthika Mohan, Judea Pearl:
Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data. Probabilistic and Causal Inference 2022: 413-432 - [p4]Elias Bareinboim, Jin Tian, Judea Pearl:
Recovering from Selection Bias in Causal and Statistical Inference. Probabilistic and Causal Inference 2022: 433-450 - [p3]Judea Pearl, Elias Bareinboim:
External Validity: From Do-Calculus to Transportability Across Populations. Probabilistic and Causal Inference 2022: 451-482 - [p2]Judea Pearl:
Detecting Latent Heterogeneity. Probabilistic and Causal Inference 2022: 483-506 - [i60]Scott Mueller, Judea Pearl:
Personalized Decision Making - A Conceptual Introduction. CoRR abs/2208.09558 (2022) - [i59]Ang Li, Judea Pearl:
Probabilities of Causation with Nonbinary Treatment and Effect. CoRR abs/2208.09568 (2022) - [i58]Ang Li, Judea Pearl:
Unit Selection with Nonbinary Treatment and Effect. CoRR abs/2208.09569 (2022) - [i57]Ang Li, Ruirui Mao, Judea Pearl:
Probabilities of Causation: Adequate Size of Experimental and Observational Samples. CoRR abs/2210.05027 (2022) - [i56]Ang Li, Judea Pearl:
Unit Selection: Case Study and Comparison with A/B Test Heuristic. CoRR abs/2210.05030 (2022) - [i55]Ang Li, Song Jiang, Yizhou Sun, Judea Pearl:
Unit Selection: Learning Benefit Function from Finite Population Data. CoRR abs/2210.08203 (2022) - [i54]Ang Li, Song Jiang, Yizhou Sun, Judea Pearl:
Learning Probabilities of Causation from Finite Population Data. CoRR abs/2210.08453 (2022) - [i53]Ang Li, Judea Pearl:
Probabilities of Causation: Role of Observational Data. CoRR abs/2210.08874 (2022) - 2021
- [c129]Chi Zhang, Carlos Cinelli, Bryant Chen, Judea Pearl:
Exploiting Equality Constraints in Causal Inference. AISTATS 2021: 1630-1638 - [i52]Scott Mueller, Ang Li, Judea Pearl:
Causes of Effects: Learning individual responses from population data. CoRR abs/2104.13730 (2021) - [i51]Ang Li, Judea Pearl:
Bounds on Causal Effects and Application to High Dimensional Data. CoRR abs/2106.12121 (2021) - [i50]Ang Li, Judea Pearl:
Unit Selection with Causal Diagram. CoRR abs/2109.07556 (2021) - 2020
- [c128]Chi Zhang, Bryant Chen, Judea Pearl:
A Simultaneous Discover-Identify Approach to Causal Inference in Linear Models. AAAI 2020: 10318-10325
2010 – 2019
- 2019
- [j86]Judea Pearl:
The seven tools of causal inference, with reflections on machine learning. Commun. ACM 62(3): 54-60 (2019) - [c127]Judea Pearl:
What is Causal Inference? AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c126]Judea Pearl:
The new science of cause and effect, with reflections on data science and artificial intelligence. IEEE BigData 2019: 4 - [c125]Carlos Cinelli, Daniel Kumor, Bryant Chen, Judea Pearl, Elias Bareinboim:
Sensitivity Analysis of Linear Structural Causal Models. ICML 2019: 1252-1261 - [c124]Ang Li, Judea Pearl:
Unit Selection Based on Counterfactual Logic. IJCAI 2019: 1793-1799 - 2018
- [c123]Karthika Mohan, Felix Thömmes, Judea Pearl:
Estimation with Incomplete Data: The Linear Case. IJCAI 2018: 5082-5088 - [c122]Karthika Mohan, Judea Pearl:
Consistent Estimation given Missing Data. PGM 2018: 284-295 - [c121]Judea Pearl:
Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution. WSDM 2018: 3 - [i49]Judea Pearl:
Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution. CoRR abs/1801.04016 (2018) - 2017
- [c120]Andrew Forney, Judea Pearl, Elias Bareinboim:
Counterfactual Data-Fusion for Online Reinforcement Learners. ICML 2017: 1156-1164 - 2016
- [j85]Elias Bareinboim, Judea Pearl:
Causal inference and the data-fusion problem. Proc. Natl. Acad. Sci. USA 113(27): 7345-7352 (2016) - [j84]Kun Zhang, Jiuyong Li
, Elias Bareinboim, Bernhard Schölkopf, Judea Pearl:
Preface to the ACM TIST Special Issue on Causal Discovery and Inference. ACM Trans. Intell. Syst. Technol. 7(2): 17:1-17:3 (2016) - [c119]Bryant Chen, Judea Pearl, Elias Bareinboim:
Incorporating Knowledge into Structural Equation Models Using Auxiliary Variables. IJCAI 2016: 3577-3583 - 2015
- [c118]Karthika Mohan, Judea Pearl:
Missing Data from a Causal Perspective. AMBN@JSAI-isAI 2015: 184-195 - [c117]Elias Bareinboim, Andrew Forney, Judea Pearl:
Bandits with Unobserved Confounders: A Causal Approach. NIPS 2015: 1342-1350 - [c116]Guy Van den Broeck, Karthika Mohan, Arthur Choi, Adnan Darwiche, Judea Pearl:
Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data. UAI 2015: 161-170 - [c115]Ilya Shpitser, Karthika Mohan, Judea Pearl:
Missing Data as a Causal and Probabilistic Problem. UAI 2015: 802-811 - [i48]Judea Pearl, Elias Bareinboim:
External Validity: From Do-Calculus to Transportability Across Populations. CoRR abs/1503.01603 (2015) - [i47]Bryant Chen, Judea Pearl, Elias Bareinboim:
Identification by Auxiliary Instrumental Sets in Linear Structural Equation Models. CoRR abs/1511.02995 (2015) - 2014
- [j83]Elias Bareinboim, Judea Pearl:
Generalizing causal knowledge: theory and algorithms. AI Matters 1(2): 11-13 (2014) - [c114]Elias Bareinboim, Jin Tian, Judea Pearl:
Recovering from Selection Bias in Causal and Statistical Inference. AAAI 2014: 2410-2416 - [c113]Bryant Chen, Jin Tian, Judea Pearl:
Testable Implications of Linear Structural Equation Models. AAAI 2014: 2424-2430 - [c112]Eunice Yuh-Jie Chen, Judea Pearl:
Random Bayesian networks with bounded indegree. AISTATS 2014: 114-121 - [c111]Karthika Mohan, Judea Pearl:
On the Testability of Models with Missing Data. AISTATS 2014: 643-650 - [c110]Elias Bareinboim, Judea Pearl:
Transportability from Multiple Environments with Limited Experiments: Completeness Results. NIPS 2014: 280-288 - [c109]Karthika Mohan, Judea Pearl:
Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data. NIPS 2014: 1520-1528 - [p1]Judea Pearl:
Graphical Models for Probabilistic and Causal Reasoning. Computing Handbook, 3rd ed. (1) 2014: 44: 1-24 - [i46]Arthur L. Delcher, Adam J. Grove, Simon Kasif, Judea Pearl:
Logarithmic-Time Updates and Queries in Probabilistic Networks. CoRR abs/1408.1479 (2014) - [i45]Guy Van den Broeck, Karthika Mohan, Arthur Choi, Judea Pearl:
Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data. CoRR abs/1411.7014 (2014) - 2013
- [j82]Judea Pearl:
Structural Counterfactuals: A Brief Introduction. Cogn. Sci. 37(6): 977-985 (2013) - [c108]Elias Bareinboim, Judea Pearl:
Causal Transportability with Limited Experiments. AAAI 2013: 95-101 - [c107]Elias Bareinboim, Judea Pearl:
Meta-Transportability of Causal Effects: A Formal Approach. AISTATS 2013: 135-143 - [c106]Eunice Yuh-Jie Chen, Judea Pearl:
A simple criterion for controlling selection bias. AISTATS 2013: 170-177 - [c105]Elias Bareinboim, Sanghack Lee, Vasant G. Honavar, Judea Pearl:
Transportability from Multiple Environments with Limited Experiments. NIPS 2013: 136-144 - [c104]Karthika Mohan, Judea Pearl, Jin Tian:
Graphical Models for Inference with Missing Data. NIPS 2013: 1277-1285 - [i44]Blai Bonet, Judea Pearl:
Qualitative MDPs and POMDPs: An Order-Of-Magnitude Approximation. CoRR abs/1301.0557 (2013) - [i43]Carlos Brito, Judea Pearl:
Generalized Instrumental Variables. CoRR abs/1301.0560 (2013) - [i42]Jin Tian, Judea Pearl:
On the Testable Implications of Causal Models with Hidden Variables. CoRR abs/1301.0608 (2013) - [i41]Joseph Y. Halpern, Judea Pearl:
Causes and Explanations: A Structural-Model Approach --- Part 1: Causes. CoRR abs/1301.2275 (2013) - [i40]Judea Pearl:
Direct and Indirect Effects. CoRR abs/1301.2300 (2013) - [i39]Jin Tian, Judea Pearl:
Causal Discovery from Changes. CoRR abs/1301.2312 (2013) - [i38]Jin Tian, Judea Pearl:
Probabilities of Causation: Bounds and Identification. CoRR abs/1301.3898 (2013) - [i37]Judea Pearl, Rina Dechter:
Identifying Independencies in Causal Graphs with Feedback. CoRR abs/1302.3595 (2013) - [i36]Alexander Balke, Judea Pearl:
Counterfactuals and Policy Analysis in Structural Models. CoRR abs/1302.4929 (2013) - [i35]David Galles, Judea Pearl:
Testing Identifiability of Causal Effects. CoRR abs/1302.4948 (2013) - [i34]Judea Pearl:
On the Testability of Causal Models with Latent and Instrumental Variables. CoRR abs/1302.4976 (2013) - [i33]Judea Pearl, James M. Robins:
Probabilistic Evaluation of Sequential Plans from Causal Models with Hidden Variables. CoRR abs/1302.4977 (2013) - [i32]Alexander Balke, Judea Pearl:
Counterfactual Probabilities: Computational Methods, Bounds and Applications. CoRR abs/1302.6784 (2013) - [i31]Dan Geiger, Azaria Paz, Judea Pearl:
On Testing Whether an Embedded Bayesian Network Represents a Probability Model. CoRR abs/1302.6809 (2013) - [i30]Judea Pearl:
A Probabilistic Calculus of Actions. CoRR abs/1302.6835 (2013) - [i29]Judea Pearl:
From Conditional Oughts to Qualitative Decision Theory. CoRR abs/1303.1455 (2013) - [i28]Tom S. Verma, Judea Pearl:
Deciding Morality of Graphs is NP-complete. CoRR abs/1303.1501 (2013) - [i27]Moisés Goldszmidt, Judea Pearl:
Reasoning With Qualitative Probabilities Can Be Tractable. CoRR abs/1303.5406 (2013) - [i26]Tom S. Verma, Judea Pearl:
An Algorithm for Deciding if a Set of Observed Independencies Has a Causal Explanation. CoRR abs/1303.5435 (2013) - [i25]Tom S. Verma, Judea Pearl:
On the Equivalence of Causal Models. CoRR abs/1304.1108 (2013) - [i24]Dan Geiger, Tom S. Verma, Judea Pearl:
d-Separation: From Theorems to Algorithms. CoRR abs/1304.1505 (2013) - [i23]Moisés Goldszmidt, Judea Pearl:
Deciding Consistency of Databases Containing Defeasible and Strict Information. CoRR abs/1304.1507 (2013) - [i22]Dan Geiger, Judea Pearl:
On the Logic of Causal Models. CoRR abs/1304.2355 (2013) - [i21]Tom S. Verma, Judea Pearl:
Causal Networks: Semantics and Expressiveness. CoRR abs/1304.2379 (2013) - [i20]Judea Pearl:
Do We Need Higher-Order Probabilities and, If So, What Do They Mean? CoRR abs/1304.2716 (2013) - [i19]Lei Xu, Judea Pearl:
Structuring Causal Tree Models with Continuous Variables. CoRR abs/1304.2730 (2013) - [i18]George Rebane, Judea Pearl:
The Recovery of Causal Poly-Trees from Statistical Data. CoRR abs/1304.2736 (2013) - [i17]Judea Pearl:
Distributed Revision of Belief Commitment in Multi-Hypothesis Interpretations. CoRR abs/1304.3102 (2013) - [i16]Igor Roizen, Judea Pearl:
Learning Link-Probabilities in Causal Trees. CoRR abs/1304.3103 (2013) - [i15]Judea Pearl:
A Constraint Propagation Approach to Probabilistic Reasoning. CoRR abs/1304.3422 (2013) - [i14]Elias Bareinboim, Judea Pearl:
A General Algorithm for Deciding Transportability of Experimental Results. CoRR abs/1312.7485 (2013) - 2012
- [c103]Elias Bareinboim, Judea Pearl:
Transportability of Causal Effects: Completeness Results. AAAI 2012: 698-704 - [c102]Barbara J. Grosz, Edward A. Feigenbaum, Marvin Minsky, Judea Pearl, Raj Reddy:
Human and Machine Intelligence. ACM-TURING 2012: 4:1 - [c101]Judea Pearl:
The Do-Calculus Revisited. UAI 2012: 3-11 - [c100]Elias Bareinboim, Judea Pearl:
Causal Inference by Surrogate Experiments: z-Identifiability. UAI 2012: 113-120 - [c99]Elias Bareinboim, Judea Pearl:
Controlling Selection Bias in Causal Inference. AISTATS 2012: 100-108 - [i13]Judea Pearl:
On a Class of Bias-Amplifying Variables that Endanger Effect Estimates. CoRR abs/1203.3503 (2012) - [i12]Judea Pearl:
On Measurement Bias in Causal Inference. CoRR abs/1203.3504 (2012) - [i11]Judea Pearl, Azaria Paz:
Confounding Equivalence in Causal Inference. CoRR abs/1203.3505 (2012) - [i10]Ilya Shpitser, Judea Pearl:
Effects of Treatment on the Treated: Identification and Generalization. CoRR abs/1205.2615 (2012) - [i9]Ilya Shpitser, Judea Pearl:
What Counterfactuals Can Be Tested. CoRR abs/1206.5294 (2012) - [i8]Carlos Brito, Judea Pearl:
Graphical Condition for Identification in recursive SEM. CoRR abs/1206.6821 (2012) - [i7]Ilya Shpitser, Judea Pearl:
Identification of Conditional Interventional Distributions. CoRR abs/1206.6876 (2012) - [i6]Judea Pearl:
Robustness of Causal Claims. CoRR abs/1207.4173 (2012) - [i5]Elias Bareinboim, Judea Pearl:
Causal Inference by Surrogate Experiments: z-Identifiability. CoRR abs/1210.4842 (2012) - [i4]Judea Pearl:
The Do-Calculus Revisited. CoRR abs/1210.4852 (2012) - 2011
- [j81]Judea Pearl:
The algorithmization of counterfactuals. Ann. Math. Artif. Intell. 61(1): 29-39 (2011) - [j80]Judea Pearl:
Graphical models, potential outcomes and causal inference: Comment on Linquist and Sobel. NeuroImage 58(3): 770-771 (2011) - [c98]Judea Pearl, Elias Bareinboim:
Transportability of Causal and Statistical Relations: A Formal Approach. AAAI 2011: 247-254 - [c97]Elias Bareinboim, Judea Pearl:
Controlling Selection Bias in Causal Inference. AAAI 2011: 1754-1755 - [c96]Judea Pearl:
The algorithmization of counterfactuals. CogSci 2011 - [c95]