Uhler, Caroline

40 publications

ICLR 2025 An Information Criterion for Controlled Disentanglement of Multimodal Data Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi Jaakkola, Caroline Uhler

ICML 2025 Probabilistic Factorial Experimental Design for Combinatorial Interventions Divya Shyamal, Jiaqi Zhang, Caroline Uhler

ICLRW 2025 Protein Structure Predictors Implicitly Define Binding Energy Functions Divya Nori, Anisha Parsan, Caroline Uhler, Wengong Jin

AISTATS 2025 Synthetic Potential Outcomes and Causal Mixture Identifiability Bijan Mazaheri, Chandler Squires, Caroline Uhler

NeurIPSW 2024 An Information Criterion for Controlled Disentanglement of Multimodal Data Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi Jaakkola, Caroline Uhler

AISTATS 2024 Causal Discovery Under Off-Target Interventions Davin Choo, Kirankumar Shiragur, Caroline Uhler

ICML 2024 Causal Discovery with Fewer Conditional Independence Tests Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler

CLeaR 2024 Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models Álvaro Ribot, Chandler Squires, Caroline Uhler

NeurIPS 2024 Identifiability Guarantees for Causal Disentanglement from Purely Observational Data Ryan Welch, Jiaqi Zhang, Caroline Uhler

NeurIPS 2024 Learning Mixtures of Unknown Causal Interventions Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler

AISTATS 2024 Membership Testing in Markov Equivalence Classes via Independence Queries Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler

ICLR 2024 Removing Biases from Molecular Representations via Information Maximization Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola

ICLRW 2024 Season Combinatorial Intervention Predictions with Salt & Peper Thomas Gaudelet, Alice Del Vecchio, Eli M Carrami, Juliana Cudini, Chantriolnt-Andreas Kapourani, Caroline Uhler, Lindsay Edwards

NeurIPS 2023 Identifiability Guarantees for Causal Disentanglement from Soft Interventions Jiaqi Zhang, Kristjan Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler

ICML 2023 Linear Causal Disentanglement via Interventions Chandler Squires, Anna Seigal, Salil S Bhate, Caroline Uhler

NeurIPS 2023 Meek Separators and Their Applications in Targeted Causal Discovery Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler

NeurIPSW 2023 Removing Biases from Molecular Representations via Information Maximization Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi Jaakkola

NeurIPSW 2023 SE(3) Denoising Score Matching for Unsupervised Binding Energy Prediction and Nanobody Design Wengong Jin, Caroline Uhler, Nir Hacohen

NeurIPS 2023 Unpaired Multi-Domain Causal Representation Learning Nils Sturma, Chandler Squires, Mathias Drton, Caroline Uhler

NeurIPS 2023 Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation Wengong Jin, Siranush Sarkizova, Xun Chen, Nir HaCohen, Caroline Uhler

CLeaR 2022 Causal Imputation via Synthetic Interventions Chandler Squires, Dennis Shen, Anish Agarwal, Devavrat Shah, Caroline Uhler

CLeaR 2022 Causal Structure Discovery Between Clusters of Nodes Induced by Latent Factors Chandler Squires, Annie Yun, Eshaan Nichani, Raj Agrawal, Caroline Uhler

JMLR 2022 Joint Inference of Multiple Graphs from Matrix Polynomials Madeline Navarro, Yuhao Wang, Antonio G. Marques, Caroline Uhler, Santiago Segarra

NeurIPS 2021 Matching a Desired Causal State via Shift Interventions Jiaqi Zhang, Chandler Squires, Caroline Uhler

CVPR 2021 Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis Karren Yang, Samuel Goldman, Wengong Jin, Alex X. Lu, Regina Barzilay, Tommi Jaakkola, Caroline Uhler

NeurIPS 2021 Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning Scott Sussex, Caroline Uhler, Andreas Krause

UAI 2020 Anchored Causal Inference in the Presence of Measurement Error Basil Saeed, Anastasiya Belyaeva, Yuhao Wang, Caroline Uhler

ICML 2020 Causal Structure Discovery from Distributions Arising from Mixtures of DAGs Basil Saeed, Snigdha Panigrahi, Caroline Uhler

AISTATS 2020 Learning High-Dimensional Gaussian Graphical Models Under Total Positivity Without Adjustment of Tuning Parameters Yuhao Wang, Uma Roy, Caroline Uhler

AISTATS 2020 Ordering-Based Causal Structure Learning in the Presence of Latent Variables Daniel Bernstein, Basil Saeed, Chandler Squires, Caroline Uhler

UAI 2020 Permutation-Based Causal Structure Learning with Unknown Intervention Targets Chandler Squires, Yuhao Wang, Caroline Uhler

AISTATS 2019 ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery Raj Agrawal, Chandler Squires, Karren Yang, Karthikeyan Shanmugam, Caroline Uhler

ICMLW 2019 Memorization in Overparameterized Autoencoders Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler

ICLR 2019 Scalable Unbalanced Optimal Transport Using Generative Adversarial Networks Karren D. Yang, Caroline Uhler

AISTATS 2019 Size of Interventional Markov Equivalence Classes in Random DAG Models Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires, Caroline Uhler

ICML 2018 Characterizing and Learning Equivalence Classes of Causal DAGs Under Interventions Karren Yang, Abigail Katcoff, Caroline Uhler

NeurIPS 2018 Direct Estimation of Differences in Causal Graphs Yuhao Wang, Chandler Squires, Anastasiya Belyaeva, Caroline Uhler

ICML 2018 Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models Raj Agrawal, Caroline Uhler, Tamara Broderick

UAI 2017 Counting Markov Equivalence Classes by Number of Immoralities Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler

NeurIPS 2017 Permutation-Based Causal Inference Algorithms with Interventions Yuhao Wang, Liam Solus, Karren Yang, Caroline Uhler