| 2025 | AISTATS | Synthetic Potential Outcomes and Causal Mixture Identifiability. | Bijan Mazaheri, Chandler Squires, Caroline Uhler |
| 2025 | ICLR | An Information Criterion for Controlled Disentanglement of Multimodal Data. | Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi S. Jaakkola, Caroline Uhler |
| 2025 | ICML | Probabilistic Factorial Experimental Design for Combinatorial Interventions. | Divya Shyamal, Jiaqi Zhang, Caroline Uhler |
| 2025 | KDD | Causality - Exploiting Multi-Modal Data. | Caroline Uhler |
| 2024 | AISTATS | Causal Discovery under Off-Target Interventions. | Davin Choo, Kirankumar Shiragur, Caroline Uhler |
| 2024 | AISTATS | Membership Testing in Markov Equivalence Classes via Independence Queries. | Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler |
| 2024 | ICLR | Removing Biases from Molecular Representations via Information Maximization. | Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola |
| 2024 | ICML | Causal Discovery with Fewer Conditional Independence Tests. | Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler |
| 2023 | ICML | Linear Causal Disentanglement via Interventions. | Chandler Squires, Anna Seigal, Salil S. Bhate, Caroline Uhler |
| 2021 | CVPR | Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis. | Karren D. Yang, Samuel Goldman, Wengong Jin, Alex X. Lu, Regina Barzilay, Tommi S. Jaakkola, Caroline Uhler |
| 2020 | AISTATS | Learning High-dimensional Gaussian Graphical Models under Total Positivity without Adjustment of Tuning Parameters. | Yuhao Wang, Uma Roy, Caroline Uhler |
| 2020 | AISTATS | Ordering-Based Causal Structure Learning in the Presence of Latent Variables. | Daniel Irving Bernstein, Basil Saeed, Chandler Squires, Caroline Uhler |
| 2020 | ICML | Causal Structure Discovery from Distributions Arising from Mixtures of DAGs. | Basil Saeed, Snigdha Panigrahi, Caroline Uhler |
| 2020 | UAI | Anchored Causal Inference in the Presence of Measurement Error. | Basil Saeed, Anastasiya Belyaeva, Yuhao Wang, Caroline Uhler |
| 2020 | UAI | Permutation-Based Causal Structure Learning with Unknown Intervention Targets. | Chandler Squires, Yuhao Wang, Caroline Uhler |
| 2019 | AISTATS | ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery. | Raj Agrawal, Chandler Squires, Karren D. Yang, Karthikeyan Shanmugam, Caroline Uhler |
| 2019 | AISTATS | Size of Interventional Markov Equivalence Classes in random DAG models. | Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires, Caroline Uhler |
| 2019 | ICLR | Scalable Unbalanced Optimal Transport using Generative Adversarial Networks. | Karren D. Yang, Caroline Uhler |
| 2018 | ICML | Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models. | Raj Agrawal, Caroline Uhler, Tamara Broderick |
| 2018 | ICML | Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions. | Karren D. Yang, Abigail Katoff, Caroline Uhler |
| 2017 | ACSSC | Joint inference of networks from stationary graph signals. | Santiago Segarra, Yuhao Wang, Caroline Uhler, Antonio G. Marques |
| 2017 | UAI | Counting Markov Equivalence Classes by Number of Immoralities. | Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler |
| 2014 | PSD | Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases. | Fei Yu, Michal Rybr, Caroline Uhler, Stephen E. Fienberg |
| 2011 | ICDM | Privacy Preserving GWAS Data Sharing. | Stephen E. Fienberg, Aleksandra B. Slavkovic, Caroline Uhler |