Caroline Uhler
33 papers · 2017–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (8) π Academic Marathon (8) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (12)
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Cross-Pollinator
(12)
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Renaissance Researcher
(8)
πΊοΈ
Taxonomy Completionist
(40)
π¬
Deep Specialist
(18)
π€
Dynamic Duo
(13)
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Triple Crown
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Keyword Champion
(2)
π§¬
Topic Evolution
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Century Club
(33)
ποΈ
Keyword Collector
(103)
π₯
Unstoppable
(9)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Trend Setter
Conferences
NIPS (10)
AISTATS (7)
ICML (6)
CLEAR (3)
ICLR (3)
UAI (2)
CVPR (1)
JMLR (1)
Top co-authors
Keywords
causal discovery
(11)
causal inference
(8)
causal graph
(6)
markov equivalence class
(6)
interventional datum
(6)
directed acyclic graph
(6)
latent variable
(5)
gene regulatory network
(4)
causal structure discovery
(3)
structure learning
(3)
causal structure learning
(3)
graphical model
(3)
causal disentanglement
(3)
causal dag
(2)
experimental design
(2)
approximation algorithm
(2)
causal model
(2)
causal structure
(2)
latent factor model
(2)
targeted causal discovery
(2)
Papers
Probabilistic Factorial Experimental Design for Combinatorial Interventions
ICML 2025
Synthetic Potential Outcomes and Causal Mixture Identifiability
AISTATS 2025
An Information Criterion for Controlled Disentanglement of Multimodal Data
ICLR 2025
Membership Testing in Markov Equivalence Classes via Independence Queries
AISTATS 2024
Causal Discovery under Off-Target Interventions
AISTATS 2024
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data
NIPS 2024
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models
CLEAR 2024
Removing Biases from Molecular Representations via Information Maximization
ICLR 2024
Causal Discovery with Fewer Conditional Independence Tests
ICML 2024
Learning Mixtures of Unknown Causal Interventions
NIPS 2024
Linear Causal Disentanglement via Interventions
ICML 2023
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation
NIPS 2023
Unpaired Multi-Domain Causal Representation Learning
NIPS 2023
Meek Separators and Their Applications in Targeted Causal Discovery
NIPS 2023
Identifiability Guarantees for Causal Disentanglement from Soft Interventions
NIPS 2023
Joint Inference of Multiple Graphs from Matrix Polynomials
JMLR 2022
Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors
CLEAR 2022
Causal Imputation via Synthetic Interventions
CLEAR 2022
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning
NIPS 2021
Matching a Desired Causal State via Shift Interventions
NIPS 2021
Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis
CVPR 2021
Permutation-Based Causal Structure Learning with Unknown Intervention Targets
UAI 2020
Learning High-dimensional Gaussian Graphical Models under Total Positivity without Adjustment of Tuning Parameters
AISTATS 2020
Ordering-Based Causal Structure Learning in the Presence of Latent Variables
AISTATS 2020
Causal Structure Discovery from Distributions Arising from Mixtures of DAGs
ICML 2020
Anchored Causal Inference in the Presence of Measurement Error
UAI 2020
Size of Interventional Markov Equivalence Classes in random DAG models
AISTATS 2019
Scalable Unbalanced Optimal Transport using Generative Adversarial Networks
ICLR 2019
ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery
AISTATS 2019
Direct Estimation of Differences in Causal Graphs
NIPS 2018
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models
ICML 2018
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
ICML 2018
Permutation-based Causal Inference Algorithms with Interventions
NIPS 2017