My research interests lie at the interface of statistics and machine learning. My current research focuses on distributional learning, causality, robustness, as well as climate applications.
I will be joining the Department of Statistics at the University of Washington as an assistant professor in fall 2025.
Distributional Principal Autoencoders X. Shen, N. Meinshausen (2024)
paper | code | slides
Causality-Oriented Robustness: Exploiting General Additive Interventions X. Shen, P. Bühlmann, A. Taeb (2023)
paper | code | slides
Asymptotic Statistical Analysis of f-divergence GAN X. Shen, K. Chen, T. Zhang (2022)
paper
To ArXiv or not to ArXiv: A Study Quantifying Pros and Cons of Posting Preprints
C. Rastogi, I. Stelmakh, X. Shen, M. Meila, F. Echenique, S. Chawla, N. B Shah (2022)
paper
Bidirectional Generative Modeling Using Adversarial Gradient Estimation X. Shen, T. Zhang, K. Chen (2020)
paper | code
Journal Publications:
Engression: Extrapolation through the Lens of Distributional Regression X. Shen, N. Meinshausen
Journal of the Royal Statistical Society Series B, to appear | paper | code | slides
Invariant Probabilistic Prediction
A. Henzi, X. Shen, M. Law, P. Bühlmann
Biometrika, to appear | paper | code | slides
Weakly Supervised Disentangled Generative Causal Representation Learning X. Shen, F. Liu, H. Dong, Q. Lian, Z. Chen, T. Zhang
Journal of Machine Learning Research, vol. 23, pp. 1-55, 2022 | paper | code | slides
Surprise Sampling: Improving and Extending the Local Case-Control Sampling X. Shen, K. Chen, W. Yu
Electron. J. Statist., vol. 15, pp. 2454-2482, 2021 | paper
Phytodiversity is associated with habitat heterogeneity from Eurasia to the Hengduan Mountains
Y. Chang, K. Gelwick, S. Willett, X. Shen, C. Albouy, A. Luo, Z. Wang, N. Zimmermann, L. Pellissier
New Phytologist, 2023 | paper
In vivo single-cell lineage tracing in zebrafish using high-resolution infrared laser-mediated gene induction microscopy
S. He, Y. Tian, S. Feng, Y. Wu, X. Shen, K. Chen, Y. He, et al.
Elife, vol. 9, e52024, 2020 | paper
Conference Publications:
Covariate-Shift Generalization via Random Sample Weighting
Y. He, X. Shen, R. Xu, T. Zhang, Y. Jiang, W. Zou, P. Cui
AAAI, 2023 | paper
Reframed GES with a Neural Conditional Dependence Measure X. Shen, S. Zhu, J. Zhang, S. Hu, Z. Chen
UAI, 2022 | paper | code
TILGAN: Transformer-based Implicit Latent GAN for Diverse and Coherent Text Generation
S. Diao*, X. Shen*, K. S. Shum, Y. Song, T. Zhang
Findings of ACL, 2021 (*equal contribution) | paper | code
CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models
M. Yang, F. Liu, Z. Chen, X. Shen, J. Hao, J. Wang
CVPR, 2021 | paper | code
Thesis:
PhD Thesis: Statistical and Structural Properties of Generative Models