default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDCaroline Uhler
Person information
- affiliation: Massachusetts Institute of Technology, USA
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[c33]Davin Choo, Kirankumar Shiragur, Caroline Uhler:
Causal Discovery under Off-Target Interventions. AISTATS 2024: 1621-1629- [c32]Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler:
Membership Testing in Markov Equivalence Classes via Independence Queries. AISTATS 2024: 3925-3933 - [c31]Alvaro Ribot
, Chandler Squires, Caroline Uhler:
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models. CLeaR 2024: 1141-1175 - [c30]Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola:
Removing Biases from Molecular Representations via Information Maximization. ICLR 2024 - [c29]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Causal Discovery with Fewer Conditional Independence Tests. ICML 2024 - [i42]Davin Choo, Kirankumar Shiragur, Caroline Uhler:
Causal Discovery under Off-Target Interventions. CoRR abs/2402.08229 (2024) - [i41]Alvaro Ribot, Chandler Squires, Caroline Uhler:
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models. CoRR abs/2402.14777 (2024) - [i40]Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler:
Membership Testing in Markov Equivalence Classes via Independence Query Oracles. CoRR abs/2403.05759 (2024) - [i39]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) - [i38]Bijan Mazaheri, Chandler Squires, Caroline Uhler:
Synthetic Potential Outcomes for Mixtures of Treatment Effects. CoRR abs/2405.19225 (2024) - [i37]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Causal Discovery with Fewer Conditional Independence Tests. CoRR abs/2406.01823 (2024) - 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) - [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 - [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
- [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) - [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 - [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] - [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
- [j13]Anastasiya Belyaeva, Chandler Squires, Caroline Uhler:
DCI: learning causal differences between gene regulatory networks. Bioinform. 37(18): 3067-3069 (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 - [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
- [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) - [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 - [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)
2010 – 2019
- 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) - [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 - [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
- [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) - [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 - [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
- [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 - [i5]Adityanarayanan Radhakrishnan, Charles Durham, Ali Soylemezoglu, Caroline Uhler:
Patchnet: Interpretable Neural Networks for Image Classification. CoRR abs/1705.08078 (2017) - 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) - [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 - [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
- [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) - [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) - 2011
- [c1]Stephen E. Fienberg, Aleksandra B. Slavkovic, Caroline Uhler:
Privacy Preserving GWAS Data Sharing. ICDM Workshops 2011: 628-635
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 22:08 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
