Detection of PVC by using a wavelet-based statistical ECG monitoring procedure. - Yonghan Jung; Heeyoung Kim (Biomed. Signal Process. Control., 2017)

Estimating Causal Effects Using Weighting-Based Estimators. - Yonghan Jung; Jin Tian 001; Elias Bareinboim (AAAI, 2020)

Learning Causal Effects via Weighted Empirical Risk Minimization. - Yonghan Jung; Jin Tian 001; Elias Bareinboim (NeurIPS, 2020)

Estimating Identifiable Causal Effects through Double Machine Learning. - Yonghan Jung; Jin Tian 001; Elias Bareinboim (AAAI, 2021)

Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning. - Yonghan Jung; Jin Tian 001; Elias Bareinboim (ICML, 2021)

Double Machine Learning Density Estimation for Local Treatment Effects with Instruments. - Yonghan Jung; Jin Tian 001; Elias Bareinboim (NeurIPS, 2021)

On Measuring Causal Contributions via do-interventions. - Yonghan Jung; Shiva Prasad Kasiviswanathan; Jin Tian 001; Dominik Janzing; Patrick Blöbaum; Elias Bareinboim (ICML, 2022)

Estimating Joint Treatment Effects by Combining Multiple Experiments. - Yonghan Jung; Jin Tian 001; Elias Bareinboim (ICML, 2023)

Estimating Causal Effects Identifiable from a Combination of Observations and Experiments. - Yonghan Jung; Ivan Diaz; Jin Tian 001; Elias Bareinboim (NeurIPS, 2023)

Unified Covariate Adjustment for Causal Inference. - Yonghan Jung; Jin Tian 001; Elias Bareinboim (NeurIPS, 2024)

Efficient Policy Evaluation Across Multiple Different Experimental Datasets. - Yonghan Jung; Alexis Bellot (NeurIPS, 2024)

Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference. - Yonghan Jung; Min Woo Park; Sanghack Lee (NeurIPS, 2024)

Sufficient Invariant Learning for Distribution Shift. - Taero Kim; Subeen Park; Sungjun Lim 002; Yonghan Jung; Krikamol Muandet; Kyungwoo Song (CVPR, 2025)

Path-specific effects for pulse-oximetry guided decisions in critical care. - Kevin Zhang; Yonghan Jung; Divyat Mahajan; Karthikeyan Shanmugam; Shalmali Joshi (CoRR, 2025)