| Graphical models for processing missing data K Mohan, J Pearl Journal of the American Statistical Association 116 (534), 1023-1037, 2021 | 240 | 2021 |
| Graphical models for inference with missing data K Mohan Advances in Neural Information Processing Systems 26 (NIPS 2013) 26, 2013 | 229 | 2013 |
| Graphical representation of missing data problems F Thoemmes, K Mohan Structural Equation Modeling: A Multidisciplinary Journal 22 (4), 631-642, 2015 | 96 | 2015 |
| Causal discovery in the presence of missing data R Tu, C Zhang, P Ackermann, K Mohan, H Kjellström, K Zhang The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 94 | 2019 |
| Graphical models for recovering probabilistic and causal queries from missing data K Mohan, J Pearl Advances in Neural Information Processing Systems (Neurips-2014), 2014 | 68* | 2014 |
| Missing Data as a Causal and Probabilistic Problem. I Shpitser, K Mohan, J Pearl UAI, 802-811, 2015 | 66 | 2015 |
| On the testability of models with missing data K Mohan, J Pearl Artificial Intelligence and Statistics, 643-650, 2014 | 45 | 2014 |
| Efficient algorithms for Bayesian network parameter learning from incomplete data GV Broeck, K Mohan, A Choi, J Pearl arXiv preprint arXiv:1411.7014, 2014 | 43 | 2014 |
| Estimation with incomplete data: The linear case K Mohan, F Thoemmes, J Pearl Proceedings of the International Joint Conferences on Artificial …, 2018 | 34 | 2018 |
| Recoverability and testability of missing data: Introduction and summary of results J Pearl, K Mohan | 28 | 2013 |
| 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 | 19 | 2022 |
| Missing data as a causal inference problem K Mohan, J Pearl, T Jin Proceedings of the neural information processing systems conference (nips), 2013 | 18 | 2013 |
| An efficient method for bayesian network parameter learning from incomplete data K Mohan, G Van den Brock, A Choi, J Pearl Causal Modeling and Machine Learning Workshop 951, 2014, 2014 | 7 | 2014 |
| Causal inference under interference and model uncertainty C Zhang, K Mohan, J Pearl Conference on Causal Learning and Reasoning, 371-385, 2023 | 6 | 2023 |
| Do finetti: On causal effects for exchangeable data S Guo, C Zhang, K Mohan, F Huszár, B Schölkopf Advances in Neural Information Processing Systems 37, 127317-127345, 2024 | 1 | 2024 |
| Causal inference with non-iid data under model uncertainty C Zhang, K Mohan, J Pearl Proceedings of Machine Learning Research vol TBD 1, 14, 2023 | 1 | 2023 |
| Causal graphs for missing data: A gentle introduction K Mohan Probabilistic and Causal Inference: The Works of Judea Pearl, 655-666, 2022 | 1 | 2022 |
| Causal Discovery with Adaptable AI Agents M Ceriscioli, K Mohan AAAI 2025 Workshop on Artificial Intelligence with Causal Techniques, 2025 | | 2025 |
| On Quantifying Bias in Causal Effects When Data Are Non-IID C Zhang, K Mohan, J Pearl | | 2022 |
| Graphical Models for R Probabilistic, M Data, K Mohan, J Pearl Probabilistic and Causal Inference: The Works of Judea Pearl, 413, 2022 | | 2022 |
