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ORCIDCaroline Uhler
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- affiliation: Massachusetts Institute of Technology, USA
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Journal Articles
- 2023
[j20]Chandler Squires, Caroline Uhler:
Causal Structure Learning: A Combinatorial Perspective. Found. Comput. Math. 23(5): 1781-1815 (2023)- [j19]Jiaqi Zhang
, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler:
Active learning for optimal intervention design in causal models. Nat. Mac. Intell. 5(10): 1066-1075 (2023) - 2022
- [j18]Elina Robeva, Bernd Sturmfels, Caroline Uhler:
Publisher Correction: Geometry of Log-Concave Density Estimation. Discret. Comput. Geom. 68(2): 645 (2022) - [j17]Madeline Navarro, Yuhao Wang, Antonio G. Marques, Caroline Uhler, Santiago Segarra:
Joint Inference of Multiple Graphs from Matrix Polynomials. J. Mach. Learn. Res. 23: 76:1-76:35 (2022) - [j16]Pantelis-Rafail Vlachas, Georgios Arampatzis, Caroline Uhler, Petros Koumoutsakos:
Multiscale simulations of complex systems by learning their effective dynamics. Nat. Mach. Intell. 4(4): 359-366 (2022) - [j15]Caroline Uhler, G. V. Shivashankar:
Machine Learning Approaches to Single-Cell Data Integration and Translation. Proc. IEEE 110(5): 557-576 (2022) - [j14]Anastasiya Belyaeva, Kaie Kubjas, Lawrence J. Sun, Caroline Uhler:
Identifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometry. SIAM J. Math. Data Sci. 4(1): 204-228 (2022) - 2021
- [j13]Anastasiya Belyaeva, Chandler Squires, Caroline Uhler:
DCI: learning causal differences between gene regulatory networks. Bioinform. 37(18): 3067-3069 (2021) - 2020
- [j12]Bernd Sturmfels, Caroline Uhler, Piotr Zwiernik:
Brownian motion tree models are toric. Kybernetika 56(6): 1154-1175 (2020) - [j11]Karren D. Yang, Karthik Damodaran, Saradha Venkatachalapathy, Ali Soylemezoglu, G. V. Shivashankar, Caroline Uhler:
Predicting cell lineages using autoencoders and optimal transport. PLoS Comput. Biol. 16(4) (2020) - [j10]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Overparameterized neural networks implement associative memory. Proc. Natl. Acad. Sci. USA 117(44): 27162-27170 (2020) - 2019
- [j9]Elina Robeva, Bernd Sturmfels, Caroline Uhler:
Geometry of Log-Concave Density Estimation. Discret. Comput. Geom. 61(1): 136-160 (2019) - [j8]Elisa Perrone, Liam Solus, Caroline Uhler:
Geometry of discrete copulas. J. Multivar. Anal. 172: 162-179 (2019) - 2018
- [j7]Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler:
Counting Markov equivalence classes for DAG models on trees. Discret. Appl. Math. 244: 170-185 (2018) - [j6]Fatemeh Mohammadi, Caroline Uhler, Charles Wang, Josephine Yu:
Generalized Permutohedra from Probabilistic Graphical Models. SIAM J. Discret. Math. 32(1): 64-93 (2018) - 2015
- [j5]Anna Klimova, Caroline Uhler, Tamás Rudas:
Faithfulness and learning hypergraphs from discrete distributions. Comput. Stat. Data Anal. 87: 57-72 (2015) - 2014
- [j4]Shaowei Lin, Caroline Uhler, Bernd Sturmfels, Peter Bühlmann:
Hypersurfaces and Their Singularities in Partial Correlation Testing. Found. Comput. Math. 14(5): 1079-1116 (2014) - [j3]Fei Yu, Stephen E. Fienberg, Aleksandra B. Slavkovic, Caroline Uhler:
Scalable privacy-preserving data sharing methodology for genome-wide association studies. J. Biomed. Informatics 50: 133-141 (2014) - 2013
- [j2]Caroline Uhler, Aleksandra B. Slavkovic, Stephen E. Fienberg:
Privacy-Preserving Data Sharing for Genome-Wide Association Studies. J. Priv. Confidentiality 5(1) (2013) - [j1]Caroline Uhler, Stephen J. Wright:
Packing Ellipsoids with Overlap. SIAM Rev. 55(4): 671-706 (2013)
Conference and Workshop Papers
- 2024
- [c35]Davin Choo, Kirankumar Shiragur, Caroline Uhler:
Causal Discovery under Off-Target Interventions. AISTATS 2024: 1621-1629 - [c34]Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler:
Membership Testing in Markov Equivalence Classes via Independence Queries. AISTATS 2024: 3925-3933 - [c33]Alvaro Ribot, Chandler Squires, Caroline Uhler:
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models. CLeaR 2024: 1141-1175 - [c32]Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola:
Removing Biases from Molecular Representations via Information Maximization. ICLR 2024 - [c31]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Causal Discovery with Fewer Conditional Independence Tests. ICML 2024 - [c30]Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler:
Learning Mixtures of Unknown Causal Interventions. NeurIPS 2024 - [c29]Ryan Welch, Jiaqi Zhang, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data. NeurIPS 2024 - 2023
- [c28]Chandler Squires, Anna Seigal, Salil S. Bhate, Caroline Uhler:
Linear Causal Disentanglement via Interventions. ICML 2023: 32540-32560 - [c27]Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler:
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation. NeurIPS 2023 - [c26]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Meek Separators and Their Applications in Targeted Causal Discovery. NeurIPS 2023 - [c25]Nils Sturma, Chandler Squires, Mathias Drton, Caroline Uhler:
Unpaired Multi-Domain Causal Representation Learning. NeurIPS 2023 - [c24]Jiaqi Zhang, Kristjan H. Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Soft Interventions. NeurIPS 2023 - 2022
- [c23]Chandler Squires, Annie Yun, Eshaan Nichani, Raj Agrawal, Caroline Uhler:
Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors. CLeaR 2022: 669-687 - [c22]Chandler Squires, Dennis Shen, Anish Agarwal, Devavrat Shah, Caroline Uhler:
Causal Imputation via Synthetic Interventions. CLeaR 2022: 688-711 - 2021
- [c21]Karren D. Yang, Samuel Goldman, Wengong Jin, Alex X. Lu, Regina Barzilay, Tommi S. Jaakkola, Caroline Uhler:
Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis. CVPR 2021: 6688-6698 - [c20]Scott Sussex, Caroline Uhler, Andreas Krause:
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. NeurIPS 2021: 777-788 - [c19]Jiaqi Zhang, Chandler Squires, Caroline Uhler:
Matching a Desired Causal State via Shift Interventions. NeurIPS 2021: 19923-19934 - 2020
- [c18]Yuhao Wang, Uma Roy, Caroline Uhler:
Learning High-dimensional Gaussian Graphical Models under Total Positivity without Adjustment of Tuning Parameters. AISTATS 2020: 2698-2708 - [c17]Daniel Irving Bernstein, Basil Saeed, Chandler Squires, Caroline Uhler:
Ordering-Based Causal Structure Learning in the Presence of Latent Variables. AISTATS 2020: 4098-4108 - [c16]Basil Saeed, Snigdha Panigrahi, Caroline Uhler:
Causal Structure Discovery from Distributions Arising from Mixtures of DAGs. ICML 2020: 8336-8345 - [c15]Basil Saeed, Anastasiya Belyaeva, Yuhao Wang, Caroline Uhler:
Anchored Causal Inference in the Presence of Measurement Error. UAI 2020: 619-628 - [c14]Chandler Squires, Yuhao Wang, Caroline Uhler:
Permutation-Based Causal Structure Learning with Unknown Intervention Targets. UAI 2020: 1039-1048 - 2019
- [c13]Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires, Caroline Uhler:
Size of Interventional Markov Equivalence Classes in random DAG models. AISTATS 2019: 3234-3243 - [c12]Raj Agrawal, Chandler Squires, Karren D. Yang, Karthikeyan Shanmugam, Caroline Uhler:
ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery. AISTATS 2019: 3400-3409 - [c11]Karren D. Yang, Caroline Uhler:
Scalable Unbalanced Optimal Transport using Generative Adversarial Networks. ICLR (Poster) 2019 - 2018
- [c10]Raj Agrawal, Caroline Uhler, Tamara Broderick:
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models. ICML 2018: 89-98 - [c9]Karren D. Yang, Abigail Katoff, Caroline Uhler:
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions. ICML 2018: 5537-5546 - [c8]Yuhao Wang, Chandler Squires, Anastasiya Belyaeva, Caroline Uhler:
Direct Estimation of Differences in Causal Graphs. NeurIPS 2018: 3774-3785 - 2017
- [c7]Santiago Segarra, Yuhao Wang, Caroline Uhler, Antonio G. Marques:
Joint inference of networks from stationary graph signals. ACSSC 2017: 975-979 - [c6]Anastasiya Belyaeva, Saradha Venkatachalapathy, Mallika Nagarajan, G. V. Shivashankar, Caroline Uhler:
Network Analysis Identifies Regulatory Hotspots in Regions of Chromosome Interactions. BCB 2017: 606 - [c5]Yuhao Wang, Liam Solus, Karren D. Yang, Caroline Uhler:
Permutation-based Causal Inference Algorithms with Interventions. NIPS 2017: 5822-5831 - [c4]Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler:
Counting Markov Equivalence Classes by Number of Immoralities. UAI 2017 - 2014
- [c3]Mabel Iglesias Ham, Michael Kerber, Caroline Uhler:
Sphere Packing with Limited Overlap. CCCG 2014 - [c2]Fei Yu, Michal Rybár, Caroline Uhler, Stephen E. Fienberg:
Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases. Privacy in Statistical Databases 2014: 170-184 - 2011
- [c1]Stephen E. Fienberg, Aleksandra B. Slavkovic, Caroline Uhler:
Privacy Preserving GWAS Data Sharing. ICDM Workshops 2011: 628-635
Editorship
- 2022
- [e1]Bernhard Schölkopf, Caroline Uhler, Kun Zhang:
1st Conference on Causal Learning and Reasoning, CLeaR 2022, Sequoia Conference Center, Eureka, CA, USA, 11-13 April, 2022. Proceedings of Machine Learning Research 177, PMLR 2022 [contents]
Informal and Other Publications
- 2025
- [i46]Luka Kovacevic, Thomas Gaudelet, James Opzoomer, Hagen Triendl, John Whittaker, Caroline Uhler, Lindsay Edwards, Jake P. Taylor-King:
No Foundations without Foundations - Why semi-mechanistic models are essential for regulatory biology. CoRR abs/2501.19178 (2025) - 2024
- [i45]Davin Choo, Kirankumar Shiragur, Caroline Uhler:
Causal Discovery under Off-Target Interventions. CoRR abs/2402.08229 (2024) - [i44]Alvaro Ribot, Chandler Squires, Caroline Uhler:
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models. CoRR abs/2402.14777 (2024) - [i43]Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler:
Membership Testing in Markov Equivalence Classes via Independence Query Oracles. CoRR abs/2403.05759 (2024) - [i42]Thomas Gaudelet, Alice Del Vecchio, Eli M. Carrami, Juliana Cudini, Chantriolnt-Andreas Kapourani, Caroline Uhler, Lindsay Edwards:
Season combinatorial intervention predictions with Salt & Peper. CoRR abs/2404.16907 (2024) - [i41]Bijan Mazaheri, Chandler Squires, Caroline Uhler:
Synthetic Potential Outcomes for Mixtures of Treatment Effects. CoRR abs/2405.19225 (2024) - [i40]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Causal Discovery with Fewer Conditional Independence Tests. CoRR abs/2406.01823 (2024) - [i39]Ryan Welch, Jiaqi Zhang, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data. CoRR abs/2410.23620 (2024) - [i38]Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi S. Jaakkola, Caroline Uhler:
An Information Criterion for Controlled Disentanglement of Multimodal Data. CoRR abs/2410.23996 (2024) - [i37]Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler:
Learning Mixtures of Unknown Causal Interventions. CoRR abs/2411.00213 (2024) - 2023
- [i36]Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler:
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation. CoRR abs/2301.10814 (2023) - [i35]Nils Sturma, Chandler Squires, Mathias Drton, Caroline Uhler:
Unpaired Multi-Domain Causal Representation Learning. CoRR abs/2302.00993 (2023) - [i34]Jiaqi Zhang, Chandler Squires, Kristjan H. Greenewald, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Soft Interventions. CoRR abs/2307.06250 (2023) - [i33]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Meek Separators and Their Applications in Targeted Causal Discovery. CoRR abs/2310.20075 (2023) - [i32]Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola:
Removing Biases from Molecular Representations via Information Maximization. CoRR abs/2312.00718 (2023) - 2022
- [i31]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Wide and Deep Neural Networks Achieve Optimality for Classification. CoRR abs/2204.14126 (2022) - [i30]Chandler Squires, Caroline Uhler:
Causal Structure Learning: a Combinatorial Perspective. CoRR abs/2206.01152 (2022) - [i29]Jiaqi Zhang, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler:
Active Learning for Optimal Intervention Design in Causal Models. CoRR abs/2209.04744 (2022) - [i28]Adityanarayanan Radhakrishnan, Max Ruiz Luyten, Neha Prasad, Caroline Uhler:
Transfer Learning with Kernel Methods. CoRR abs/2211.00227 (2022) - [i27]Anna Seigal, Chandler Squires, Caroline Uhler:
Linear Causal Disentanglement via Interventions. CoRR abs/2211.16467 (2022) - 2021
- [i26]Scott Sussex, Andreas Krause, Caroline Uhler:
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. CoRR abs/2105.14024 (2021) - [i25]Saachi Jain, Adityanarayanan Radhakrishnan, Caroline Uhler:
A Mechanism for Producing Aligned Latent Spaces with Autoencoders. CoRR abs/2106.15456 (2021) - [i24]Jiaqi Zhang, Chandler Squires, Caroline Uhler:
Matching a Desired Causal State via Shift Interventions. CoRR abs/2107.01850 (2021) - [i23]Adityanarayanan Radhakrishnan, George Stefanakis, Mikhail Belkin, Caroline Uhler:
Simple, Fast, and Flexible Framework for Matrix Completion with Infinite Width Neural Networks. CoRR abs/2108.00131 (2021) - [i22]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Local Quadratic Convergence of Stochastic Gradient Descent with Adaptive Step Size. CoRR abs/2112.14872 (2021) - 2020
- [i21]Basil Saeed, Snigdha Panigrahi, Caroline Uhler:
Causal Structure Discovery from Distributions Arising from Mixtures of DAGs. CoRR abs/2001.11940 (2020) - [i20]Adityanarayanan Radhakrishnan, Eshaan Nichani, Daniel Irving Bernstein, Caroline Uhler:
Balancedness and Alignment are Unlikely in Linear Neural Networks. CoRR abs/2003.06340 (2020) - [i19]Karren D. Yang, Samuel Goldman, Wengong Jin, Alex Lu, Regina Barzilay, Tommi S. Jaakkola, Caroline Uhler:
Improved Conditional Flow Models for Molecule to Image Synthesis. CoRR abs/2006.08532 (2020) - [i18]Pantelis-Rafail Vlachas, Georgios Arampatzis, Caroline Uhler, Petros Koumoutsakos:
Learning the Effective Dynamics of Complex Multiscale Systems. CoRR abs/2006.13431 (2020) - [i17]Neha Prasad, Karren D. Yang, Caroline Uhler:
Optimal Transport using GANs for Lineage Tracing. CoRR abs/2007.12098 (2020) - [i16]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Linear Convergence and Implicit Regularization of Generalized Mirror Descent with Time-Dependent Mirrors. CoRR abs/2009.08574 (2020) - [i15]Madeline Navarro, Yuhao Wang, Antonio G. Marques, Caroline Uhler, Santiago Segarra:
Joint Inference of Multiple Graphs from Matrix Polynomials. CoRR abs/2010.08120 (2020) - [i14]Eshaan Nichani, Adityanarayanan Radhakrishnan, Caroline Uhler:
Do Deeper Convolutional Networks Perform Better? CoRR abs/2010.09610 (2020) - [i13]Chandler Squires, Joshua Amaniampong, Caroline Uhler:
Efficient Permutation Discovery in Causal DAGs. CoRR abs/2011.03610 (2020) - 2019
- [i12]Karren D. Yang, Caroline Uhler:
Multi-Domain Translation by Learning Uncoupled Autoencoders. CoRR abs/1902.03515 (2019) - [i11]Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires, Caroline Uhler:
Size of Interventional Markov Equivalence Classes in Random DAG Models. CoRR abs/1903.02054 (2019) - [i10]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Overparameterized Neural Networks Can Implement Associative Memory. CoRR abs/1909.12362 (2019) - [i9]Daniel Irving Bernstein, Basil Saeed, Chandler Squires, Caroline Uhler:
Ordering-Based Causal Structure Learning in the Presence of Latent Variables. CoRR abs/1910.09014 (2019) - 2018
- [i8]Raj Agrawal, Tamara Broderick, Caroline Uhler:
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models. CoRR abs/1803.05554 (2018) - [i7]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Downsampling leads to Image Memorization in Convolutional Autoencoders. CoRR abs/1810.10333 (2018) - [i6]Karren D. Yang, Caroline Uhler:
Scalable Unbalanced Optimal Transport using Generative Adversarial Networks. CoRR abs/1810.11447 (2018) - 2017
- [i5]Adityanarayanan Radhakrishnan, Charles Durham, Ali Soylemezoglu, Caroline Uhler:
Patchnet: Interpretable Neural Networks for Image Classification. CoRR abs/1705.08078 (2017) - 2014
- [i4]Mabel Iglesias Ham, Michael Kerber, Caroline Uhler:
Sphere Packing with Limited Overlap. CoRR abs/1401.0468 (2014) - [i3]Fei Yu, Michal Rybár, Caroline Uhler, Stephen E. Fienberg:
Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases. CoRR abs/1407.8067 (2014) - 2013
- [i2]Garvesh Raskutti, Caroline Uhler:
Learning directed acyclic graphs based on sparsest permutations. CoRR abs/1307.0366 (2013) - 2012
- [i1]Caroline Uhler, Aleksandra B. Slavkovic, Stephen E. Fienberg:
Privacy-Preserving Data Sharing for Genome-Wide Association Studies. CoRR abs/1205.0739 (2012)
Coauthor Index
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