Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning Y Zhang, Q Tang, Y Zhang, J Wang, U Stimming, AA Lee
Nature communications 11 (1), 1706, 2020
1117 2020 VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain J Yoon, Y Zhang, J Jordon, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 2020
293 2020 Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning Y Zhang, AA Lee
Chemical Science 10 (35), 8154-8163, 2019
148 2019 Learning Overlapping Representations for the Estimation of Individualized Treatment Effects Y Zhang, A Bellot, M van der Schaar
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
118 2020 CASTLE: Regularization via Auxiliary Causal Graph Discovery T Kyono*, Y Zhang*, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 2020
81 2020 Energy–entropy competition and the effectiveness of stochastic gradient descent in machine learning Y Zhang, AM Saxe, MS Advani, AA Lee
Molecular Physics 116 (21-22), 3214-3223, 2018
76 2018 MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms T Kyono*, Y Zhang*, A Bellot, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 2021
65 2021 What is a randomization test? Y Zhang, Q Zhao
Journal of the American Statistical Association 118 (544), 2928-2942, 2023
33 2023 Geometry of energy landscapes and the optimizability of deep neural networks S Becker, Y Zhang, AA Lee
Physical Review Letters, 2018
32 2018 SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes Z Qian, Y Zhang, I Bica, A Wood, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 2021
29 2021 Learning outside the Black-Box: The pursuit of interpretable models J Crabbe, Y Zhang, W Zame, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 2020
29 2020 Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification HS Lee*, Y Zhang*, W Zame, C Shen, JW Lee, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 2020
21 2020 Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning Y Zhang, D Jarrett, M van der Schaar
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
13 2020 Sharp bounds and semiparametric inference in -and -sensitivity analysis for observational studies Y Zhang, Q Zhao
arXiv preprint arXiv:2211.04697, 2024
8 2024 Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects Y Zhang*, J Berrevoets*, M van der Schaar
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
8 2021 Multiple conditional randomization tests for lagged and spillover treatment effects Y Zhang, Q Zhao
Biometrika, 2023
7 * 2023 Gradient Regularized V-Learning for Dynamic Treatment Regimes Y Zhang, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 2020
6 2020 - and -sensitivity analysis for causal inference with unmeasured confoundingY Zhang, Q Zhao
arXiv preprint arXiv:2211.04697, 2022
3 2022 Posterior conformal prediction Y Zhang, EJ Candès
arXiv preprint arXiv:2409.19712, 2024
1 2024