| Year |
Citation |
Score |
| 2019 |
Pearl J, Bareinboim E. Note on ''Generalizability of Study Results''. Epidemiology (Cambridge, Mass.). 30: 186-188. PMID 30721164 DOI: 10.1097/Ede.0000000000000939 |
0.692 |
|
| 2016 |
Bareinboim E, Pearl J. Causal inference and the data-fusion problem. Proceedings of the National Academy of Sciences of the United States of America. 113: 7345-52. PMID 27382148 DOI: 10.1073/Pnas.1510507113 |
0.733 |
|
| 2016 |
Hannart A, Pearl J, Otto FEL, Naveau P, Ghil M. Causal counterfactual theory for the attribution of weather and climate-related events Bulletin of the American Meteorological Society. 97: 99-110. DOI: 10.1175/Bams-D-14-00034.1 |
0.318 |
|
| 2016 |
Zhang K, Li J, Bareinboim E, Schölkopf B, Pearl J. Preface to the ACM TIST Special Issue on Causal Discovery and Inference Acm Transactions On Intelligent Systems and Technology. 7: 1-3. DOI: 10.1145/2840720 |
0.707 |
|
| 2015 |
Pearl J. Causes of Effects and Effects of Causes Sociological Methods and Research. 44: 149-164. DOI: 10.1177/0049124114562614 |
0.371 |
|
| 2015 |
Bareinboim E, Forney A, Pearl J. Bandits with unobserved confounders: A causal approach Advances in Neural Information Processing Systems. 2015: 1342-1350. |
0.726 |
|
| 2015 |
Shpitser I, Mohan K, Pearl J. Missing data as a causal and probabilistic problem Uncertainty in Artificial Intelligence - Proceedings of the 31st Conference, Uai 2015. 802-811. |
0.6 |
|
| 2014 |
Pearl J. Reply to commentary by Imai, Keele, Tingley, and Yamamoto concerning causal mediation analysis. Psychological Methods. 19: 488-92. PMID 25486117 DOI: 10.1037/Met0000022 |
0.36 |
|
| 2014 |
Pearl J. Interpretation and identification of causal mediation. Psychological Methods. 19: 459-81. PMID 24885338 DOI: 10.1037/A0036434 |
0.378 |
|
| 2014 |
Pearl J. TRYGVE HAAVELMO AND THE EMERGENCE OF CAUSAL CALCULUS Econometric Theory. DOI: 10.2139/Ssrn.2338247 |
0.337 |
|
| 2014 |
Pearl J, Bareinboim E. External validity: From do-calculus to transportability across populations Statistical Science. 29: 579-595. DOI: 10.1214/14-Sts486 |
0.718 |
|
| 2014 |
Bareinboim E, Pearl J. Generalizing causal knowledge Ai Matters. 1: 11-13. DOI: 10.1145/2685328.2685331 |
0.676 |
|
| 2014 |
Kuroki M, Pearl J. Measurement bias and effect restoration in causal inference Biometrika. 101: 423-437. DOI: 10.1093/Biomet/Ast066 |
0.374 |
|
| 2014 |
Chen B, Tian J, Pearl J. Testable implications of linear structural equation models Proceedings of the National Conference On Artificial Intelligence. 4: 2424-2430. |
0.466 |
|
| 2014 |
Bareinboim E, Pearl J. Transportability from multiple environments with limited experiments: Completeness results Advances in Neural Information Processing Systems. 1: 280-288. |
0.713 |
|
| 2014 |
Bareinboim E, Tian J, Pearl J. Recovering from selection bias in causal and statistical inference Proceedings of the National Conference On Artificial Intelligence. 4: 2410-2416. |
0.748 |
|
| 2013 |
Pearl J. Comment on ‘Causal inference, probability theory, and graphical insights’ by Stuart G. Baker. Statistics in Medicine. 32: 4331-3. PMID 25564689 DOI: 10.1002/Sim.5901 |
0.359 |
|
| 2013 |
Pearl J. Structural counterfactuals: a brief introduction. Cognitive Science. 37: 977-85. PMID 23927018 DOI: 10.1111/Cogs.12065 |
0.338 |
|
| 2013 |
Bareinboim E, Pearl J. A General Algorithm for Deciding Transportability of Experimental Results Journal of Causal Inference. 1. DOI: 10.1515/Jci-2012-0004 |
0.742 |
|
| 2013 |
Bareinboim E, Pearl J. Meta-transportability of causal effects: A formal approach Journal of Machine Learning Research. 31: 135-143. |
0.715 |
|
| 2013 |
Mohan K, Pearl J, Tian J. Graphical models for inference with missing data Advances in Neural Information Processing Systems. |
0.484 |
|
| 2013 |
Bareinboim E, Pearl J. Causal transportability with limited experiments Proceedings of the 27th Aaai Conference On Artificial Intelligence, Aaai 2013. 95-101. |
0.729 |
|
| 2012 |
Pearl J. The causal mediation formula--a guide to the assessment of pathways and mechanisms. Prevention Science : the Official Journal of the Society For Prevention Research. 13: 426-36. PMID 22419385 DOI: 10.1007/S11121-011-0270-1 |
0.339 |
|
| 2012 |
Pearl J, Kim JH. Studies in semi-admissible heuristics. Ieee Transactions On Pattern Analysis and Machine Intelligence. 4: 392-9. PMID 21869053 DOI: 10.1109/Tpami.1982.4767270 |
0.304 |
|
| 2012 |
Bareinboim E, Brito C, Pearl J. Local characterizations of causal Bayesian networks Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7205: 1-17. DOI: 10.1007/978-3-642-29449-5_1 |
0.667 |
|
| 2012 |
Bareinboim E, Pearl J. Causal inference by surrogate experiments: Z-identifiability Uncertainty in Artificial Intelligence - Proceedings of the 28th Conference, Uai 2012. 113-120. |
0.708 |
|
| 2012 |
Bareinboim E, Pearl J. Controlling selection bias in causal inference Journal of Machine Learning Research. 22: 100-108. |
0.711 |
|
| 2012 |
Bareinboim E, Pearl J. Transportability of causal effects: Completeness results Proceedings of the National Conference On Artificial Intelligence. 1: 698-704. |
0.723 |
|
| 2011 |
Pearl J. Invited commentary: understanding bias amplification. American Journal of Epidemiology. 174: 1223-7; discussion p. PMID 22034488 DOI: 10.1093/Aje/Kwr352 |
0.314 |
|
| 2011 |
Pearl J. Principal stratification--a goal or a tool? The International Journal of Biostatistics. 7: 20. PMID 21556288 DOI: 10.2202/1557-4679.1322 |
0.318 |
|
| 2011 |
Pearl J. Statistics and causality: separated to reunite-commentary on Bryan Dowd's "separated at birth". Health Services Research. 46: 421-9. PMID 21371028 DOI: 10.1111/J.1475-6773.2011.01243.X |
0.332 |
|
| 2011 |
Greenland S, Pearl J. Adjustments and their Consequences-Collapsibility Analysis using Graphical Models International Statistical Review. 79: 401-426. DOI: 10.1111/J.1751-5823.2011.00158.X |
0.328 |
|
| 2011 |
Pearl J, Bareinboim E. Transportability of causal and statistical relations: A formal approach Proceedings - Ieee International Conference On Data Mining, Icdm. 540-547. DOI: 10.1109/ICDMW.2011.169 |
0.681 |
|
| 2011 |
Pearl J. The algorithmization of counterfactuals Annals of Mathematics and Artificial Intelligence. 61: 29-39. DOI: 10.1007/S10472-011-9247-9 |
0.355 |
|
| 2010 |
Pearl J. On the consistency rule in causal inference: axiom, definition, assumption, or theorem? Epidemiology (Cambridge, Mass.). 21: 872-5. PMID 20864888 DOI: 10.1097/Ede.0B013E3181F5D3Fd |
0.329 |
|
| 2010 |
Pearl J. The Foundations Of Causal Inference Sociological Methodology. 40: 75-149. DOI: 10.1111/J.1467-9531.2010.01228.X |
0.353 |
|
| 2009 |
Pearl J. Causal inference in statistics: An overview Statistics Surveys. 3: 96-146. DOI: 10.1214/09-Ss057 |
0.386 |
|
| 2009 |
Shpitser I, Pearl J. Effects of treatment on the treated: Identification and generalization Proceedings of the 25th Conference On Uncertainty in Artificial Intelligence, Uai 2009. 514-521. |
0.551 |
|
| 2008 |
Cai Z, Kuroki M, Pearl J, Tian J. Bounds on direct effects in the presence of confounded intermediate variables. Biometrics. 64: 695-701. PMID 18162106 DOI: 10.1111/J.1541-0420.2007.00949.X |
0.526 |
|
| 2008 |
Shpitser I, Pearl J. Complete identification methods for the causal hierarchy Journal of Machine Learning Research. 9: 1941-1979. |
0.556 |
|
| 2008 |
Shpitser I, Pearl J. Dormant independence Proceedings of the National Conference On Artificial Intelligence. 2: 1081-1087. |
0.555 |
|
| 2007 |
Shpitser I, Pearl J. What counterfactuals can be tested Proceedings of the 23rd Conference On Uncertainty in Artificial Intelligence, Uai 2007. 352-359. |
0.522 |
|
| 2006 |
Shpitser I, Pearl J. Identification of conditional interventional distributions Proceedings of the 22nd Conference On Uncertainty in Artificial Intelligence, Uai 2006. 437-444. |
0.632 |
|
| 2006 |
Shpitser I, Pearl J. Identification of joint interventional distributions in recursive semi-Markovian causal models Proceedings of the National Conference On Artificial Intelligence. 2: 1219-1226. |
0.658 |
|
| 2006 |
Tian J, Kang C, Pearl J. A characterizetion of interventional distributions in semi-markovian causal models Proceedings of the National Conference On Artificial Intelligence. 2: 1239-1244. |
0.458 |
|
| 2005 |
Pearl J. Influence Diagrams—Historical and Personal Perspectives Decision Analysis. 2: 232-234. DOI: 10.1287/Deca.1050.0055 |
0.317 |
|
| 2005 |
Halpern JY, Pearl J. Causes and explanations: A structural-model approach. Part II: Explanations British Journal For the Philosophy of Science. 56: 889-911. DOI: 10.1093/Bjps/Axi148 |
0.316 |
|
| 2005 |
Avin C, Shpitser I, Pearl J. Identifiability of path-specific effects Ijcai International Joint Conference On Artificial Intelligence. 357-363. |
0.622 |
|
| 2003 |
Pearl J. Statistics and Causal Inference: A Review Test. 12: 281-318. DOI: 10.1007/Bf02595718 |
0.362 |
|
| 2002 |
Pearl J. Reasoning with cause and effect Ai Magazine. 23: 95-111. DOI: 10.1609/Aimag.V23I1.1612 |
0.337 |
|
| 2002 |
Pearl J. A Short Rejoinder to Rejoinder International Statistical Review. 70: 214-214. DOI: 10.1111/J.1751-5823.2002.Tb00360.X |
0.317 |
|
| 2002 |
Pearl J. Comments on Nozer Singpurwalla's “On Causality and Causal Mechanisms” International Statistical Review. 70: 210-212. DOI: 10.1111/J.1751-5823.2002.Tb00358.X |
0.309 |
|
| 2002 |
Pearl J. Comments on seeing and doing International Statistical Review. 70: 207-209. DOI: 10.1111/J.1751-5823.2002.Tb00357.X |
0.354 |
|
| 2002 |
Tian J, Pearl J. A general identification condition for causal effects Proceedings of the National Conference On Artificial Intelligence. 567-573. |
0.443 |
|
| 2002 |
Tian J, Pearl J. A new characterization of the experimental implications of causal bayesian networks Proceedings of the National Conference On Artificial Intelligence. 574-579. |
0.45 |
|
| 2001 |
Pearl J. Causal inference in the health sciences: A conceptual introduction Health Services and Outcomes Research Methodology. 2: 189-220. DOI: 10.1023/A:1020315127304 |
0.327 |
|
| 2001 |
Pearl J. On two pseudo-paradoxes in Bayesian analysis Annals of Mathematics and Artificial Intelligence. 32: 171-177. DOI: 10.1023/A:1016709416174 |
0.349 |
|
| 2000 |
Pearl J. Causal Inference Without Counterfactuals: Comment Journal of the American Statistical Association. 95: 428. DOI: 10.2307/2669380 |
0.325 |
|
| 2000 |
Tian J, Pearl J. Probabilities of causation: Bounds and identification Annals of Mathematics and Artificial Intelligence. 28: 287-313. |
0.511 |
|
| 1999 |
Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research Epidemiology. 10: 37-48. PMID 9888278 DOI: 10.1097/00001648-199901000-00005 |
0.317 |
|
| 1999 |
Greenland S, Robins JM, Pearl J. Confounding and Collapsibility in Causal Inference Statistical Science. 14: 29-46. DOI: 10.1214/Ss/1009211805 |
0.348 |
|
| 1999 |
Pearl J. Synthese. 121: 93-149. DOI: 10.1023/A:1005233831499 |
0.362 |
|
| 1998 |
Galles D, Pearl J. An axiomatic characterization of causal counterfactuals Foundations of Science. 3: 151-182. DOI: 10.1023/A:1009602825894 |
0.304 |
|
| 1997 |
Subramanian D, Greiner R, Pearl J. Relevance of relevance Artificial Intelligence. 97: 1-5. DOI: 10.1016/S0004-3702(97)00075-1 |
0.318 |
|
| 1997 |
Galles D, Pearl J. Axioms of causal relevance Artificial Intelligence. 97: 9-43. DOI: 10.1016/S0004-3702(97)00047-7 |
0.346 |
|
| 1997 |
Darwiche A, Pearl J. On the logic of iterated belief revision Artificial Intelligence. 89: 1-29. DOI: 10.1016/S0004-3702(96)00038-0 |
0.339 |
|
| 1996 |
Delcher AL, Grove AJ, Kasif S, Pearl J. Logarithmic-time updates and queries in probabilistic networks Journal of Artificial Intelligence Research. 4: 37-59. DOI: 10.1613/Jair.238 |
0.304 |
|
| 1996 |
Pearl J. Structural and Probabilistic Causality Psychology of Learning and Motivation - Advances in Research and Theory. 34: 393-435. DOI: 10.1016/S0079-7421(08)60566-6 |
0.381 |
|
| 1996 |
Meiri I, Dechter R, Pearl J. Uncovering trees in constraint networks Artificial Intelligence. 86: 245-267. DOI: 10.1016/0004-3702(95)00102-6 |
0.653 |
|
| 1996 |
Goldszmidt M, Pearl J. Qualitative probabilities for default reasoning, belief revision, and causal modeling Artificial Intelligence. 84: 57-112. DOI: 10.1016/0004-3702(95)00090-9 |
0.371 |
|
| 1995 |
Pearl J. Causal diagrams for empirical research Biometrika. 82: 669-688. DOI: 10.1093/Biomet/82.4.669 |
0.368 |
|
| 1995 |
Pearl J, Verma TS. A theory of inferred causation Studies in Logic and the Foundations of Mathematics. 134: 789-811. DOI: 10.1016/S0049-237X(06)80074-1 |
0.352 |
|
| 1993 |
Goldszmidt M, Morris P, Pearl J. A maximum entropy approach to nonmonotonic reasoning Ieee Transactions On Pattern Analysis and Machine Intelligence. 15: 220-232. DOI: 10.1109/34.204904 |
0.316 |
|
| 1992 |
Geffner H, Pearl J. Conditional entailment: Bridging two approaches to default reasoning Artificial Intelligence. 53: 209-244. DOI: 10.1016/0004-3702(92)90071-5 |
0.342 |
|
| 1992 |
Dechter R, Pearl J. Structure identification in relational data Artificial Intelligence. 58: 237-270. DOI: 10.1016/0004-3702(92)90009-M |
0.68 |
|
| 1992 |
Pearl J, Verma TS. A statistical semantics for causation Statistics and Computing. 2: 91-95. DOI: 10.1007/Bf01889587 |
0.395 |
|
| 1991 |
Goldszmidt M, Pearl J. On the consistency of defeasible databases Artificial Intelligence. 52: 121-149. DOI: 10.1016/0004-3702(91)90039-M |
0.354 |
|
| 1991 |
Dechter R, Meiri I, Pearl J. Temporal constraint networks Artificial Intelligence. 49: 61-95. DOI: 10.1016/0004-3702(91)90006-6 |
0.684 |
|
| 1990 |
Pearl J. Reasoning with belief functions: An analysis of compatibility International Journal of Approximate Reasoning. 4: 363-389. DOI: 10.1016/0888-613X(90)90013-R |
0.323 |
|
| 1990 |
Geiger D, Pearl J. Logical and algorithmic properties of independence and their application to Bayesian networks Annals of Mathematics and Artificial Intelligence. 2: 165-178. DOI: 10.1007/Bf01531004 |
0.402 |
|
| 1990 |
Geiger D, Verma T, Pearl J. Identifying independence in bayesian networks Networks. 20: 507-534. DOI: 10.1002/Net.3230200504 |
0.318 |
|
| 1989 |
Dechter R, Pearl J. Tree clustering for constraint networks Artificial Intelligence. 38: 353-366. DOI: 10.1016/0004-3702(89)90037-4 |
0.649 |
|
| 1988 |
Pearl J. On probability intervals International Journal of Approximate Reasoning. 2: 211-216. DOI: 10.1016/S0888-613X(00)00027-X |
0.333 |
|
| 1987 |
Pearl J. Distributed revision of composite beliefs Artificial Intelligence. 33: 173-215. DOI: 10.1016/0004-3702(87)90034-8 |
0.359 |
|
| 1987 |
Pearl J. Evidential reasoning using stochastic simulation of causal models Artificial Intelligence. 32: 245-257. DOI: 10.1016/0004-3702(87)90012-9 |
0.308 |
|
| 1987 |
Dechter R, Pearl J. Network-based heuristics for constraint-satisfaction problems Artificial Intelligence. 34: 1-38. DOI: 10.1016/0004-3702(87)90002-6 |
0.664 |
|
| 1986 |
Pearl J, Tarsi M. Structuring causal trees Journal of Complexity. 2: 60-77. DOI: 10.1016/0885-064X(86)90023-3 |
0.319 |
|
| 1986 |
Pearl J. Fusion, propagation, and structuring in belief networks Artificial Intelligence. 29: 241-288. DOI: 10.1016/0004-3702(86)90072-X |
0.358 |
|
| 1985 |
Dechter R, Pearl J. Generalized best-first search strategies and the optimality of A* Journal of the Acm (Jacm). 32: 505-536. DOI: 10.1145/3828.3830 |
0.646 |
|
| 1983 |
Pearl J. On the Discovery and Generation of Certain Heuristics Ai Magazine. 4: 23-33. DOI: 10.1609/Aimag.V4I1.385 |
0.325 |
|
| 1983 |
Karp RM, Pearl J. Searching for an optimal path in a tree with random costs Artificial Intelligence. 21: 99-116. DOI: 10.1016/S0004-3702(83)80006-X |
0.302 |
|
| 1981 |
Burns M, Pearl J. Causal and diagnostic inferences: A comparison of validity Organizational Behavior and Human Performance. 28: 379-394. DOI: 10.1016/0030-5073(81)90005-2 |
0.354 |
|
| 1980 |
Huyn N, Dechter R, Pearl J. Probabilistic analysis of the complexity of A∗ Artificial Intelligence. 15: 241-254. DOI: 10.1016/0004-3702(80)90045-4 |
0.626 |
|
| 1978 |
Pearl J. An economic basis for certain methods of evaluating probabilistic forecasts International Journal of Man-Machine Studies. 10: 175-183. DOI: 10.1016/S0020-7373(78)80010-8 |
0.324 |
|
| 1977 |
Pearl J. On summarizing data using probabilistic assertions Ieee Transactions On Information Theory. 23: 459-465. DOI: 10.1109/Tit.1977.1055756 |
0.311 |
|
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