| Classification of short single-lead electrocardiograms (ECGs) for atrial fibrillation detection using piecewise linear spline and XGBoost Y Chen, X Wang, Y Jung, V Abedi, R Zand, M Bikak, M Adibuzzaman Physiological measurement 39 (10), 104006, 2018 | 61 | 2018 |
| Estimating Identifiable Causal Effects through Double Machine Learning Y Jung, J Tian, E Bareinboim Proceedings of the 35th AAAI Conference on Artificial Intelligence 35, 2021 | 60 | 2021 |
| Learning Causal Effects via Weighted Empirical Risk Minimization Y Jung, J Tian, E Bareinboim Proceedings of the 34th Annual Conference on Neural Information Processing …, 2020 | 51 | 2020 |
| Detection of PVC by using a wavelet-based statistical ECG monitoring procedure Y Jung, H Kim Biomedical Signal Processing and Control 36, 176-182, 2017 | 43 | 2017 |
| Estimating Causal Effects Using Weighting-Based Estimators Y Jung, J Tian, E Bareinboim Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020, 2020 | 41 | 2020 |
| On measuring causal contributions via do-interventions Y Jung, S Kasiviswanathan, J Tian, D Janzing, P Blöbaum, E Bareinboim International Conference on Machine Learning, 10476-10501, 2022 | 32 | 2022 |
| Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning Y Jung, J Tian, E Bareinboim Proceedings of the 38th International Conference on Machine Learning, 2021 | 21 | 2021 |
| Estimating Causal Effects Identifiable from a Combination of Observations and Experiments Y Jung, I Díaz, J Tian, E Bareinboim | 8 | 2023 |
| Double Machine Learning Density Estimation for Local Treatment Effects with Instruments Y Jung, J Tian, E Bareinboim Proceedings of the 35th Annual Conference on Neural Information Processing …, 2021 | 8 | 2021 |
| Estimating Joint Treatment Effects by Combining Multiple Experiments Y Jung, J Tian, E Bareinboim International Conference on Machine Learning, 15451-15527, 2023 | 5 | 2023 |
| Methods for Quantifying Efficacy-Effectiveness Gap of Randomized Controlled Trials: Examples in ARDS M Adibuzzaman, Y Jung, E Bareinboim, P Griffin, S Kethireddy, M Bikak, ... Critical Care Medicine 47 (1), 143, 2019 | 3 | 2019 |
| Regenerating evidence from landmark trials in ARDS using structural causal models on electronic health record M Bikak, M Adibuzzaman, Y Jung, Y Yih, E Bareinboim B104. CRITICAL CARE: BIG DATA IN HEALTH CARE-PREDICTIVE ANALYTICS, CLINICAL …, 2018 | 2 | 2018 |
| Sufficient Invariant Learning for Distribution Shift T Kim, S Park, S Lim, Y Jung, K Muandet, K Song arXiv preprint arXiv:2210.13533, 2024 | 1 | 2024 |
| Efficient Policy Evaluation Across Multiple Different Experimental Datasets Y Jung, A Bellot The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | | 2024 |
| Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference Y Jung, MW Park, S Lee The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | | 2024 |
| Unified Covariate Adjustment for Causal Inference Y Jung, J Tian, E Bareinboim The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | | 2024 |
| A Short Note on Finite Sample Analysis on Double/Debiased Machine Learning Y Jung https://openreview.net/forum?id=QMGWz-B5E6J, 2023 | | 2023 |
| Detection of premature ventricular contraction using wavelet-based statistical ECG monitoring Y Jung Korean Advanced Institute of Science and Technology, 2016 | | 2016 |
| Detection of Atrial Fibrillation Using Markov Regime Switching Models of Heart Rate Intervals Y Jung, H Kim Journal of Korean Institute of Industrial Engineers 42 (4), 290-295, 2016 | | 2016 |
Elias BareinboimColumbia UniversityVerified email at columbia.edu