| Causal inference with non-IID data using linear graphical models C Zhang, K Mohan, J Pearl Advances in Neural Information Processing Systems 35, 13214-13225, 2022 | 18 | 2022 |
| A simultaneous discover-identify approach to causal inference in linear models C Zhang, B Chen, J Pearl Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 10318 …, 2020 | 14 | 2020 |
| Exploiting equality constraints in causal inference C Zhang, C Cinelli, B Chen, J Pearl International Conference on Artificial Intelligence and Statistics, 1630-1638, 2021 | 6 | 2021 |
| Causal Inference under Interference and Model Uncertainty C Zhang, K Mohan, J Pearl Conference on Causal Learning and Reasoning, 371-385, 2023 | 3 | 2023 |
| Do Finetti: On Causal Effects for Exchangeable Data S Guo, C Zhang, K Mohan, F Huszár, B Schölkopf arXiv preprint arXiv:2405.18836, 2024 | 1 | 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 |
| Causal Analysis for Generalized Interference Problems C Zhang University of California, Los Angeles, 2023 | | 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 |
| On Quantifying Bias in Causal Effects When Data Are Non-IID C Zhang, K Mohan, J Pearl ICML Workshop: Beyond Bayes: Paths Towards Universal Reasoning Systems, 2022 | | 2022 |
Judea PearlProfessor of Computer Science, University of California, Los AngelesBestätigte E-Mail-Adresse bei cs.ucla.edu