Judea Pearl
27 papers · 2008–2024 · 8 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (10) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (8)
π
Academic Marathon
(16)
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Cross-Pollinator
(13)
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Renaissance Researcher
(5)
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Keyword Trendsetter Combo
(3)
π¬
Deep Specialist
(23)
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Keyword Champion
(3)
π±
Topic Pioneer
π§¬
Topic Evolution
π
Century Club
(27)
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Trend Setter
ποΈ
Keyword Collector
(91)
π₯
Unstoppable
(13)
Conferences
AISTATS (7)
NIPS (6)
AAAI (5)
IJCAI (4)
ICML (2)
CLEAR (1)
JMLR (1)
PGM (1)
Top co-authors
Research topics
Keywords
causal inference
(21)
graphical model
(11)
observational datum
(7)
causal effect
(6)
missing datum
(5)
treatment effect
(4)
linear model
(3)
unit selection
(3)
counterfactual reasoning
(3)
domain adaptation
(3)
causal identification
(2)
probabilistic modeling
(2)
structural causal model
(2)
sensitivity analysis
(2)
unobserved confounder
(2)
multi-armed bandit
(2)
missing data
(2)
do-calculus
(2)
treatment effect estimation
(2)
selection bia
(2)
Papers
Unit Selection with Nonbinary Treatment and Effect
AAAI 2024
Probabilities of Causation with Nonbinary Treatment and Effect
AAAI 2024
Probabilities of Causation: Role of Observational Data
AISTATS 2023
Causal Inference under Interference and Model Uncertainty
CLEAR 2023
Bounds on Causal Effects and Application to High Dimensional Data
AAAI 2022
Causes of Effects: Learning Individual Responses from Population Data
IJCAI 2022
Causal Inference with Non-IID Data using Linear Graphical Models
NIPS 2022
Unit Selection with Causal Diagram
AAAI 2022
Exploiting Equality Constraints in Causal Inference
AISTATS 2021
A Simultaneous Discover-Identify Approach to Causal Inference in Linear Models
AAAI 2020
Sensitivity Analysis of Linear Structural Causal Models
ICML 2019
Unit Selection Based on Counterfactual Logic
IJCAI 2019
Consistent Estimation given Missing Data
PGM 2018
Estimation with Incomplete Data: The Linear Case
IJCAI 2018
Counterfactual Data-Fusion for Online Reinforcement Learners
ICML 2017
Incorporating Knowledge into Structural Equation Models Using Auxiliary Variables
IJCAI 2016
Bandits with Unobserved Confounders: A Causal Approach
NIPS 2015
On the Testability of Models with Missing Data
AISTATS 2014
Random Bayesian networks with bounded indegree
AISTATS 2014
Transportability from Multiple Environments with Limited Experiments: Completeness Results
NIPS 2014
Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data
NIPS 2014
A simple criterion for controlling selection bias
AISTATS 2013
Graphical Models for Inference with Missing Data
NIPS 2013
Meta-Transportability of Causal Effects: A Formal Approach
AISTATS 2013
Transportability from Multiple Environments with Limited Experiments
NIPS 2013
Controlling Selection Bias in Causal Inference
AISTATS 2012
Complete Identification Methods for the Causal Hierarchy
JMLR 2008