Permutation-based causal structure learning with unknown intervention targets C Squires, Y Wang, C Uhler Conference on Uncertainty in Artificial Intelligence, 1039-1048, 2020 | 75 | 2020 |
ABCD-strategy: Budgeted experimental design for targeted causal structure discovery R Agrawal, C Squires, K Yang, K Shanmugam, C Uhler The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 71 | 2019 |
Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing A Belyaeva, L Cammarata, A Radhakrishnan, C Squires, K Dai Yang, ... Nature Communications 12 (1), 1-13, 2021 | 53 | 2021 |
Linear Causal Disentanglement via Interventions C Squires, A Seigal, SS Bhate, C Uhler International Conference on Machine Learning, 2023 | 52 | 2023 |
Ordering-based causal structure learning in the presence of latent variables D Bernstein, B Saeed, C Squires, C Uhler International Conference on Artificial Intelligence and Statistics, 4098-4108, 2020 | 51 | 2020 |
Causal structure learning: A combinatorial perspective C Squires, C Uhler Foundations of Computational Mathematics 23 (5), 1781-1815, 2023 | 41 | 2023 |
Active Structure Learning of Causal DAGs via Directed Clique Trees C Squires, S Magliacane, K Greenewald, D Katz, M Kocaoglu, ... Advances in Neural Information Processing Systems 33, 2020 | 36 | 2020 |
Direct estimation of differences in causal graphs Y Wang, C Squires, A Belyaeva, C Uhler Advances in Neural Information Processing Systems, 3770-3781, 2018 | 36 | 2018 |
Identifiability guarantees for causal disentanglement from soft interventions J Zhang, K Greenewald, C Squires, A Srivastava, K Shanmugam, C Uhler Advances in Neural Information Processing Systems 36, 2024 | 29 | 2024 |
DCI: learning causal differences between gene regulatory networks A Belyaeva, C Squires, C Uhler Bioinformatics 37 (18), 3067-3069, 2021 | 23 | 2021 |
Causal imputation via synthetic interventions C Squires, D Shen, A Agarwal, D Shah, C Uhler Conference on Causal Learning and Reasoning, 688-711, 2022 | 22 | 2022 |
Matching a desired causal state via shift interventions J Zhang, C Squires, C Uhler Advances in Neural Information Processing Systems 34, 19923-19934, 2021 | 20 | 2021 |
The DeCAMFounder: nonlinear causal discovery in the presence of hidden variables R Agrawal, C Squires, N Prasad, C Uhler Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2023 | 19 | 2023 |
Causal structure discovery between clusters of nodes induced by latent factors C Squires, A Yun, E Nichani, R Agrawal, C Uhler Conference on Causal Learning and Reasoning, 669-687, 2022 | 17 | 2022 |
Unpaired multi-domain causal representation learning N Sturma, C Squires, M Drton, C Uhler Advances in Neural Information Processing Systems 36, 2024 | 12 | 2024 |
Active learning for optimal intervention design in causal models J Zhang, L Cammarata, C Squires, TP Sapsis, C Uhler Nature Machine Intelligence, 1-10, 2023 | 11 | 2023 |
Size of interventional Markov equivalence classes in random DAG models D Katz, K Shanmugam, C Squires, C Uhler The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 9 | 2019 |
Maximum Likelihood Estimation for Brownian Motion Tree Models Based on One Sample M Truell, JC Hütter, C Squires, P Zwiernik, C Uhler arXiv preprint arXiv:2112.00816, 2021 | 8 | 2021 |
causaldag: creation, manipulation, and learning of causal models, 2018 C Squires URL https://github. com/uhlerlab/causaldag, 0 | 7 | |
Efficient Permutation Discovery in Causal DAGs C Squires, J Amaniampong, C Uhler arXiv preprint arXiv:2011.03610, 2020 | 5 | 2020 |