Chandler Squires

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Caroline UhlerMassachusetts Institute of TechnologyVerified email at mit.edu
Karthikeyan ShanmugamResearch Scientist, Google Research IndiaVerified email at google.com
Anastasiya BelyaevaGoogle ResearchVerified email at google.com
Jiaqi ZhangMITVerified email at mit.edu
Karren YangMassachusetts Institute of TechnologyVerified email at mit.edu
Yuhao Wang | 王禹皓Institute for Interdisciplinary Information Sciences, Tsinghua UniversityVerified email at tsinghua.edu.cn
Kristjan GreenewaldResearch Scientist, MIT-IBM Watson AI Lab, IBM ResearchVerified email at ibm.com
Louis CammarataStatistics PhD Candidate, Harvard UniversityVerified email at g.harvard.edu
Anna SeigalAssistant Professor of Applied Mathematics, Harvard UniversityVerified email at seas.harvard.edu
Salil BhateBroad Institute of MIT and HarvardVerified email at broadinstitute.org
Adityanarayanan RadhakrishnanBroad Institute of MIT and HarvardVerified email at mit.edu
Basil SaeedStanford UniversityVerified email at stanford.edu
GV ShivashankarETH Zurich and Paul Scherrer Institute, SwitzerlandVerified email at ethz.ch
Daniel Irving BernsteinTulane UniversityVerified email at tulane.edu
Akash SrivastavaMIT, IBM Research, University of EdinburghVerified email at mit.edu
Sara MagliacaneUniversity of AmsterdamVerified email at uva.nl
Murat KocaogluAssistant Professor, School of ECE, Purdue UniversityVerified email at purdue.edu
Themistoklis SapsisProfessor of Mechanical and Ocean Engineering, MITVerified email at mit.edu
Anish AgarwalAssistant Professor, Columbia UniversityVerified email at columbia.edu
Dennis ShenAssistant Professor at USC Data Sciences and OperationsVerified email at marshall.usc.edu

Chandler Squires

Postdoctoral Research Associate, CMU

Verified email at andrew.cmu.edu - Homepage

causality structure learning representation learning experimental design computational biology


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Permutation-based causal structure learning with unknown intervention targets C Squires, Y Wang, C Uhler Conference on Uncertainty in Artificial Intelligence, 1039-1048, 2020	92	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	80	2019
Linear Causal Disentanglement via Interventions C Squires, A Seigal, SS Bhate, C Uhler International Conference on Machine Learning, 2023	72	2023
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	58	2021
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	58	2020
Causal structure learning: A combinatorial perspective C Squires, C Uhler Foundations of Computational Mathematics 23 (5), 1781-1815, 2023	57	2023
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	55	2024
Direct estimation of differences in causal graphs Y Wang, C Squires, A Belyaeva, C Uhler Advances in Neural Information Processing Systems, 3770-3781, 2018	41	2018
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	39	2020
DCI: learning causal differences between gene regulatory networks A Belyaeva, C Squires, C Uhler Bioinformatics 37 (18), 3067-3069, 2021	28	2021
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	27	2023
Unpaired multi-domain causal representation learning N Sturma, C Squires, M Drton, C Uhler Advances in Neural Information Processing Systems 36, 2024	25	2024
Causal imputation via synthetic interventions C Squires, D Shen, A Agarwal, D Shah, C Uhler Conference on Causal Learning and Reasoning, 688-711, 2022	25	2022
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	24	2023
Matching a desired causal state via shift interventions J Zhang, C Squires, C Uhler Advances in Neural Information Processing Systems 34, 19923-19934, 2021	22	2021
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	19	2022
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	10	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	8
Efficient Permutation Discovery in Causal DAGs C Squires, J Amaniampong, C Uhler arXiv preprint arXiv:2011.03610, 2020	5	2020

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