Privacy Preserving GWAS Data Sharing. - Stephen E. Fienberg; Aleksandra B. Slavkovic; Caroline Uhler (ICDM Workshops, 2011)

Learning directed acyclic graphs based on sparsest permutations. - Garvesh Raskutti; Caroline Uhler (CoRR, 2013)

Privacy-Preserving Data Sharing for Genome-Wide Association Studies. - Caroline Uhler; Aleksandra B. Slavkovic; Stephen E. Fienberg (J. Priv. Confidentiality, 2013)

Packing Ellipsoids with Overlap. - Caroline Uhler; Stephen J. Wright 001 (SIAM Rev., 2013)

Sphere Packing with Limited Overlap. - Mabel Iglesias Ham; Michael Kerber; Caroline Uhler (CCCG, 2014)

Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases. - Fei Yu 005; Michal Rybár; Caroline Uhler; Stephen E. Fienberg (Privacy in Statistical Databases, 2014)

Hypersurfaces and Their Singularities in Partial Correlation Testing. - Shaowei Lin; Caroline Uhler; Bernd Sturmfels; Peter Bühlmann (Found. Comput. Math., 2014)

Scalable privacy-preserving data sharing methodology for genome-wide association studies. - Fei Yu 005; Stephen E. Fienberg; Aleksandra B. Slavkovic; Caroline Uhler (J. Biomed. Informatics, 2014)

Faithfulness and learning hypergraphs from discrete distributions. - Anna Klimova; Caroline Uhler; Tamás Rudas (Comput. Stat. Data Anal., 2015)

Joint inference of networks from stationary graph signals. - Santiago Segarra; Yuhao Wang 005; Caroline Uhler; Antonio G. Marques (ACSSC, 2017)

Network Analysis Identifies Regulatory Hotspots in Regions of Chromosome Interactions. - Anastasiya Belyaeva; Saradha Venkatachalapathy; Mallika Nagarajan; G. V. Shivashankar; Caroline Uhler (BCB, 2017)

Permutation-based Causal Inference Algorithms with Interventions. - Yuhao Wang 005; Liam Solus; Karren D. Yang; Caroline Uhler (NIPS, 2017)

Counting Markov Equivalence Classes by Number of Immoralities. - Adityanarayanan Radhakrishnan; Liam Solus; Caroline Uhler (UAI, 2017)

Patchnet: Interpretable Neural Networks for Image Classification. - Adityanarayanan Radhakrishnan; Charles Durham; Ali Soylemezoglu; Caroline Uhler (CoRR, 2017)

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

Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions. - Karren D. Yang; Abigail Katoff; Caroline Uhler (ICML, 2018)

Direct Estimation of Differences in Causal Graphs. - Yuhao Wang 005; Chandler Squires; Anastasiya Belyaeva; Caroline Uhler (NeurIPS, 2018)

Downsampling leads to Image Memorization in Convolutional Autoencoders. - Adityanarayanan Radhakrishnan; Mikhail Belkin; Caroline Uhler (CoRR, 2018)

Counting Markov equivalence classes for DAG models on trees. - Adityanarayanan Radhakrishnan; Liam Solus; Caroline Uhler (Discret. Appl. Math., 2018)

Generalized Permutohedra from Probabilistic Graphical Models. - Fatemeh Mohammadi; Caroline Uhler; Charles Wang; Josephine Yu (SIAM J. Discret. Math., 2018)

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

Size of Interventional Markov Equivalence Classes in random DAG models. - Dmitriy Katz; Karthikeyan Shanmugam; Chandler Squires; Caroline Uhler (AISTATS, 2019)

Scalable Unbalanced Optimal Transport using Generative Adversarial Networks. - Karren D. Yang; Caroline Uhler (ICLR (Poster), 2019)

Multi-Domain Translation by Learning Uncoupled Autoencoders. - Karren D. Yang; Caroline Uhler (CoRR, 2019)

Overparameterized Neural Networks Can Implement Associative Memory. - Adityanarayanan Radhakrishnan; Mikhail Belkin; Caroline Uhler (CoRR, 2019)

Geometry of Log-Concave Density Estimation. - Elina Robeva; Bernd Sturmfels; Caroline Uhler (Discret. Comput. Geom., 2019)

Geometry of discrete copulas. - Elisa Perrone; Liam Solus; Caroline Uhler (J. Multivar. Anal., 2019)

Learning High-dimensional Gaussian Graphical Models under Total Positivity without Adjustment of Tuning Parameters. - Yuhao Wang 005; Uma Roy; Caroline Uhler (AISTATS, 2020)

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

Causal Structure Discovery from Distributions Arising from Mixtures of DAGs. - Basil Saeed; Snigdha Panigrahi; Caroline Uhler (ICML, 2020)

Anchored Causal Inference in the Presence of Measurement Error. - Basil Saeed; Anastasiya Belyaeva; Yuhao Wang 005; Caroline Uhler (UAI, 2020)

Permutation-Based Causal Structure Learning with Unknown Intervention Targets. - Chandler Squires; Yuhao Wang 005; Caroline Uhler (UAI, 2020)

Balancedness and Alignment are Unlikely in Linear Neural Networks. - Adityanarayanan Radhakrishnan; Eshaan Nichani; Daniel Irving Bernstein; Caroline Uhler (CoRR, 2020)

Improved Conditional Flow Models for Molecule to Image Synthesis. - Karren D. Yang; Samuel Goldman; Wengong Jin; Alex Lu 002; Regina Barzilay; Tommi S. Jaakkola; Caroline Uhler (CoRR, 2020)

Learning the Effective Dynamics of Complex Multiscale Systems. - Pantelis-Rafail Vlachas; Georgios Arampatzis; Caroline Uhler; Petros Koumoutsakos (CoRR, 2020)

Optimal Transport using GANs for Lineage Tracing. - Neha Prasad; Karren D. Yang; Caroline Uhler (CoRR, 2020)

Linear Convergence and Implicit Regularization of Generalized Mirror Descent with Time-Dependent Mirrors. - Adityanarayanan Radhakrishnan; Mikhail Belkin; Caroline Uhler (CoRR, 2020)

Do Deeper Convolutional Networks Perform Better? - Eshaan Nichani; Adityanarayanan Radhakrishnan; Caroline Uhler (CoRR, 2020)

Efficient Permutation Discovery in Causal DAGs. - Chandler Squires; Joshua Amaniampong; Caroline Uhler (CoRR, 2020)

Brownian motion tree models are toric. - Bernd Sturmfels; Caroline Uhler; Piotr Zwiernik (Kybernetika, 2020)

Predicting cell lineages using autoencoders and optimal transport. - Karren D. Yang; Karthik Damodaran; Saradha Venkatachalapathy; Ali Soylemezoglu; G. V. Shivashankar; Caroline Uhler (PLoS Comput. Biol., 2020)

Overparameterized neural networks implement associative memory. - Adityanarayanan Radhakrishnan; Mikhail Belkin; Caroline Uhler (Proc. Natl. Acad. Sci. USA, 2020)

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 (CVPR, 2021)

Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. - Scott Sussex; Caroline Uhler; Andreas Krause 001 (NeurIPS, 2021)

Matching a Desired Causal State via Shift Interventions. - Jiaqi Zhang; Chandler Squires; Caroline Uhler (NeurIPS, 2021)

DCI: learning causal differences between gene regulatory networks. - Anastasiya Belyaeva; Chandler Squires; Caroline Uhler (Bioinform., 2021)

A Mechanism for Producing Aligned Latent Spaces with Autoencoders. - Saachi Jain; Adityanarayanan Radhakrishnan; Caroline Uhler (CoRR, 2021)

Simple, Fast, and Flexible Framework for Matrix Completion with Infinite Width Neural Networks. - Adityanarayanan Radhakrishnan; George Stefanakis; Mikhail Belkin; Caroline Uhler (CoRR, 2021)

Local Quadratic Convergence of Stochastic Gradient Descent with Adaptive Step Size. - Adityanarayanan Radhakrishnan; Mikhail Belkin; Caroline Uhler (CoRR, 2021)

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 (CLeaR, 2022)

Wide and Deep Neural Networks Achieve Optimality for Classification. - Adityanarayanan Radhakrishnan; Mikhail Belkin; Caroline Uhler (CoRR, 2022)

Transfer Learning with Kernel Methods. - Adityanarayanan Radhakrishnan; Max Ruiz Luyten; Neha Prasad; Caroline Uhler (CoRR, 2022)

Linear Causal Disentanglement via Interventions. - Anna Seigal; Chandler Squires; Caroline Uhler (CoRR, 2022)

Publisher Correction: Geometry of Log-Concave Density Estimation. - Elina Robeva; Bernd Sturmfels; Caroline Uhler (Discret. Comput. Geom., 2022)

Joint Inference of Multiple Graphs from Matrix Polynomials. - Madeline Navarro; Yuhao Wang 005; Antonio G. Marques; Caroline Uhler; Santiago Segarra (J. Mach. Learn. Res., 2022)

Multiscale simulations of complex systems by learning their effective dynamics. - Pantelis-Rafail Vlachas; Georgios Arampatzis; Caroline Uhler; Petros Koumoutsakos (Nat. Mach. Intell., 2022)

Machine Learning Approaches to Single-Cell Data Integration and Translation. - Caroline Uhler; G. V. Shivashankar (Proc. IEEE, 2022)

Identifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometry. - Anastasiya Belyaeva; Kaie Kubjas; Lawrence J. Sun; Caroline Uhler (SIAM J. Math. Data Sci., 2022)

Linear Causal Disentanglement via Interventions. - Chandler Squires; Anna Seigal; Salil S. Bhate; Caroline Uhler (ICML, 2023)

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

Meek Separators and Their Applications in Targeted Causal Discovery. - Kirankumar Shiragur; Jiaqi Zhang; Caroline Uhler (NeurIPS, 2023)

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

Identifiability Guarantees for Causal Disentanglement from Soft Interventions. - Jiaqi Zhang; Kristjan H. Greenewald; Chandler Squires; Akash Srivastava; Karthikeyan Shanmugam; Caroline Uhler (NeurIPS, 2023)

Causal Structure Learning: A Combinatorial Perspective. - Chandler Squires; Caroline Uhler (Found. Comput. Math., 2023)

Active learning for optimal intervention design in causal models. - Jiaqi Zhang; Louis Cammarata; Chandler Squires; Themistoklis P. Sapsis; Caroline Uhler (Nat. Mac. Intell., 2023)

Causal Discovery under Off-Target Interventions. - Davin Choo; Kirankumar Shiragur; Caroline Uhler (AISTATS, 2024)

Membership Testing in Markov Equivalence Classes via Independence Queries. - Jiaqi Zhang; Kirankumar Shiragur; Caroline Uhler (AISTATS, 2024)

Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models. - Alvaro Ribot; Chandler Squires; Caroline Uhler (CLeaR, 2024)

Removing Biases from Molecular Representations via Information Maximization. - Chenyu Wang 003; Sharut Gupta; Caroline Uhler; Tommi S. Jaakkola (ICLR, 2024)

Causal Discovery with Fewer Conditional Independence Tests. - Kirankumar Shiragur; Jiaqi Zhang; Caroline Uhler (ICML, 2024)

Learning Mixtures of Unknown Causal Interventions. - Abhinav Kumar; Kirankumar Shiragur; Caroline Uhler (NeurIPS, 2024)

Identifiability Guarantees for Causal Disentanglement from Purely Observational Data. - Ryan Welch; Jiaqi Zhang; Caroline Uhler (NeurIPS, 2024)

Membership Testing in Markov Equivalence Classes via Independence Query Oracles. - Jiaqi Zhang; Kirankumar Shiragur; Caroline Uhler (CoRR, 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 (CoRR, 2024)

Synthetic Potential Outcomes for Mixtures of Treatment Effects. - Bijan Mazaheri; Chandler Squires; Caroline Uhler (CoRR, 2024)

Synthetic Potential Outcomes and Causal Mixture Identifiability. - Bijan Mazaheri; Chandler Squires; Caroline Uhler (AISTATS, 2025)

An Information Criterion for Controlled Disentanglement of Multimodal Data. - Chenyu Wang 003; Sharut Gupta; Xinyi Zhang; Sana Tonekaboni; Stefanie Jegelka; Tommi S. Jaakkola; Caroline Uhler (ICLR, 2025)

No Foundations without Foundations - Why semi-mechanistic models are essential for regulatory biology. - Luka Kovacevic; Thomas Gaudelet; James Opzoomer; Hagen Triendl; John Whittaker; Caroline Uhler; Lindsay Edwards; Jake P. Taylor-King (CoRR, 2025)

Meta-Dependence in Conditional Independence Testing. - Bijan Mazaheri; Jiaqi Zhang; Caroline Uhler (CoRR, 2025)

BindEnergyCraft: Casting Protein Structure Predictors as Energy-Based Models for Binder Design. - Divya Nori; Anisha Parsan; Caroline Uhler; Wengong Jin (CoRR, 2025)

Probabilistic Factorial Experimental Design for Combinatorial Interventions. - Divya Shyamal; Jiaqi Zhang; Caroline Uhler (CoRR, 2025)