| Unit Selection Based on Counterfactual Logic A Li, J Pearl Twenty-Eighth International Joint Conference on Artificial Intelligence …, 2019 | 56 | 2019 |
| Causes of Effects: Learning individual responses from population data S Mueller, A Li, J Pearl Thirty-First International Joint Conference on Artificial Intelligence …, 2022 | 42 | 2022 |
| Bounds on causal effects and application to high dimensional data A Li, J Pearl Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), 2022 | 27 | 2022 |
| Unit Selection with Causal Diagram A Li, J Pearl Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), 2022 | 25 | 2022 |
| Probabilities of causation with nonbinary treatment and effect A Li, J Pearl Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 20465 …, 2024 | 17 | 2024 |
| Unit selection with nonbinary treatment and effect A Li, J Pearl Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 20473 …, 2024 | 11 | 2024 |
| Training machine learning models with causal logic A Li, S J. Chen, J Qin, Z Qin Companion Proceedings of the Web Conference 2020, 557-561, 2020 | 8 | 2020 |
| Learning probabilities of causation from finite population data A Li, S Jiang, Y Sun, J Pearl arXiv preprint arXiv:2210.08453, 2022 | 7 | 2022 |
| Probabilities of causation: Adequate size of experimental and observational samples A Li, R Mao, J Pearl arXiv preprint arXiv:2210.05027, 2022 | 6 | 2022 |
| Unit selection based on counterfactual logic A Li, J Pearl UCLA, 2021 | 6* | 2021 |
| Unit selection: Learning benefit function from finite population data A Li, S Jiang, Y Sun, J Pearl arXiv preprint arXiv:2210.08203, 2022 | 5 | 2022 |
| Unit selection: Case study and comparison with a/b test heuristic A Li, J Pearl arXiv preprint arXiv:2210.05030, 2022 | 5 | 2022 |
| Efficient learning in linearly solvable MDP models. A Li, PR Schrater Twenty-Third International Joint Conference on Artificial Intelligence …, 2013 | 5 | 2013 |
| Epsilon-identifiability of causal quantities A Li, S Mueller, J Pearl arXiv preprint arXiv:2301.12022, 2023 | 3 | 2023 |
| Probabilities of causation: Role of observational data A Li, J Pearl International Conference on Artificial Intelligence and Statistics, 10012-10027, 2023 | 2 | 2023 |
| Probabilities of Causation: Role of Observational Data A Li, J Pearl AISTATS 2023, 2022 | 2 | 2022 |
| Learning Causes of Effects and Individual Responses from Population Data and Bayesian Networks S Mueller, A Li, J Pearl | | 2024 |
| Causal AI Framework for Unit Selection in Optimizing Electric Vehicle Procurement C Zhang, A Li, S Mueller, R Iliev 2nd Workshop on Sustainable AI, 2024 | | 2024 |
| Cognitive Systems Laboratory, Department of Computer Science, University of California, Los Angeles, Los Angeles, California, USA.{angli, scott, judea}@ cs. ucla. edu A Li, S Mueller, J Pearl | | 2023 |
| Combining experimental and observational studies to estimate individual treatment effects: applications to customer journey optimization T Harinen, R Iliev, A Li, S Mueller, C Zhang KDD: 1st Workshop on End-End Customer Journey Optimization, 2022 | | 2022 |
Judea PearlProfessor of Computer Science, University of California, Los AngelesVerified email at cs.ucla.edu
