Yonghan Jung
12 papers · 2020–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (12) πΊοΈ Taxonomy Completionist (13) π£ Hot Topic Early Bird
π
Conference Polyglot
(4)
π
Academic Marathon
(5)
π¬
Deep Specialist
(10)
π
Century Club
(12)
π₯
Unstoppable
(6)
Conferences
NIPS (6)
ICML (3)
AAAI (2)
CVPR (1)
Top co-authors
Keywords
causal inference
(9)
causal effect estimation
(4)
double machine learning
(3)
interventional distribution
(2)
causal identification
(2)
graphical model
(2)
influence function
(2)
covariate adjustment
(2)
empirical risk minimization
(1)
causal effect
(1)
domain generalization
(1)
observational study
(1)
propensity score
(1)
inverse probability weighting
(1)
distribution shift
(1)
density estimation
(1)
invariant learning
(1)
external validity
(1)
treatment effect
(1)
kernel smoothing
(1)
Papers
Sufficient Invariant Learning for Distribution Shift
CVPR 2025
Unified Covariate Adjustment for Causal Inference
NIPS 2024
Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference
NIPS 2024
Efficient Policy Evaluation Across Multiple Different Experimental Datasets
NIPS 2024
Estimating Joint Treatment Effects by Combining Multiple Experiments
ICML 2023
Estimating Causal Effects Identifiable from a Combination of Observations and Experiments
NIPS 2023
On Measuring Causal Contributions via do-interventions
ICML 2022
Estimating Identifiable Causal Effects through Double Machine Learning
AAAI 2021
Double Machine Learning Density Estimation for Local Treatment Effects with Instruments
NIPS 2021
Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning
ICML 2021
Estimating Causal Effects Using Weighting-Based Estimators
AAAI 2020
Learning Causal Effects via Weighted Empirical Risk Minimization
NIPS 2020