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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
- 2022
[c132]Ang Li, Judea Pearl:
Unit Selection with Causal Diagram. AAAI 2022: 5765-5772- [c131]Ang Li, Judea Pearl:
Bounds on Causal Effects and Application to High Dimensional Data. AAAI 2022: 5773-5780 - [c130]Scott Mueller, Ang Li, Judea Pearl:
Causes of Effects: Learning Individual Responses from Population Data. IJCAI 2022: 2712-2718 - [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 Thoemmes, 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 - [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 - [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]Elias Bareinboim, Judea Pearl:
Controlling Selection Bias in Causal Inference. AAAI 2011 - [c97]Judea Pearl, Elias Bareinboim:
Transportability of Causal and Statistical Relations: A Formal Approach. AAAI 2011 - [c96]Judea Pearl:
The algorithmization of counterfactuals. CogSci 2011 - [c95]Steven A. Sloman, Judea Pearl, Nick Chater, Lance J. Rips, Jim Joyce, Stefan Kaufmann:
On Counterfactuals and Cognitive Science: Rumlhart Prize Symposium in Honor of Judea Pearl. CogSci 2011 - [c94]Elias Bareinboim, Carlos Brito, Judea Pearl:
Local Characterizations of Causal Bayesian Networks. GKR 2011: 1-17 - [c93]Judea Pearl, Elias Bareinboim:
Transportability of Causal and Statistical Relations: A Formal Approach. ICDM Workshops 2011: 540-547 - [c92]Judea Pearl:
The mathematics of causal inference. KDD 2011: 5 - [r2]Sander Greenland, Judea Pearl:
Causal Diagrams. International Encyclopedia of Statistical Science 2011: 208-216 - 2010
- [j79]Yair Weiss, Judea Pearl:
Belief propagation: technical perspective. Commun. ACM 53(10): 94 (2010) - [c91]Judea Pearl:
On a Class of Bias-Amplifying Variables that Endanger Effect Estimates. UAI 2010: 417-424 - [c90]Judea Pearl:
On Measurement Bias in Causal Inference. UAI 2010: 425-432 - [c89]Judea Pearl, Azaria Paz:
Confounding Equivalence in Causal Inference. UAI 2010: 433-441 - [c88]Judea Pearl:
Causal Inference. NIPS Causality: Objectives and Assessment 2010: 39-58
2000 – 2009
- 2009
- [c87]Ilya Shpitser, Judea Pearl:
Effects of Treatment on the Treated: Identification and Generalization. UAI 2009: 514-521 - 2008
- [j78]Ilya Shpitser, Judea Pearl:
Complete Identification Methods for the Causal Hierarchy. J. Mach. Learn. Res. 9: 1941-1979 (2008) - [c86]Ilya Shpitser, Judea Pearl:
Dormant Independence. AAAI 2008: 1081-1087 - 2007
- [j77]Mark Hopkins, Judea Pearl:
Causality and Counterfactuals in the Situation Calculus. J. Log. Comput. 17(5): 939-953 (2007) - [c85]Ilya Shpitser, Judea Pearl:
What Counterfactuals Can Be Tested. UAI 2007: 352-359 - 2006
- [c84]Ilya Shpitser, Judea Pearl:
Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models. AAAI 2006: 1219-1226 - [c83]Jin Tian, Changsung Kang, Judea Pearl:
A Characterization of Interventional Distributions in Semi-Markovian Causal Models. AAAI 2006: 1239-1244 - [c82]Carlos Brito, Judea Pearl:
Graphical Condition for Identification in recursive SEM. UAI 2006 - [c81]Ilya Shpitser, Judea Pearl:
Identification of Conditional Interventional Distributions. UAI 2006 - 2005
- [j76]Judea Pearl:
Response to review by Kyburg. Artif. Intell. 169(2): 180 (2005) - [j75]Judea Pearl:
Influence Diagrams - Historical and Personal Perspectives. Decis. Anal. 2(4): 232-234 (2005) - [c80]Chen Avin, Ilya Shpitser, Judea Pearl:
Identifiability of Path-Specific Effects. IJCAI 2005: 357-363 - 2004
- [c79]Judea Pearl:
Robustness of Causal Claims. UAI 2004: 446-453 - 2002
- [j74]Judea Pearl:
Reasoning with Cause and Effect. AI Mag. 23(1): 95-112 (2002) - [c78]Carlos Brito, Judea Pearl:
A Graphical Criterion for the Identification of Causal Effects in Linear Models. AAAI/IAAI 2002: 533-538 - [c77]Jin Tian, Judea Pearl:
A General Identification Condition for Causal Effects. AAAI/IAAI 2002: 567-573 - [c76]Jin Tian, Judea Pearl:
A New Characterization of the Experimental Implications of Causal Bayesian Networks. AAAI/IAAI 2002: 574-580 - [c75]Blai Bonet, Judea Pearl:
Qualitative MDPs and POMDPs: An Order-Of-Magnitude Approximation. UAI 2002: 61-68 - [c74]