collaborators

5 papers

stat.ML2026

Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series

Hanyang Jiang, Rina Foygel Barber, Ashwin Pananjady +1

Conformal prediction methods enjoy strong theoretical and empirical predictive inference performance, provided the data is exchangeable and is treated symmetrically during training…

stat.ME2026

Efficient First-Order Methods for Estimating Generalized Additive Index Models

Ziyu Peng, Linglingzhi Zhu, Yao Xie

Generalized additive index models (GAIMs) offer a flexible semiparametric framework for capturing complex data relationships, balancing the interpretability of parametric models wi…

cs.LG2026

Flow-based Conformal Prediction for Multi-dimensional Time Series

Junghwan Lee, Chen Xu, Yao Xie

Time series prediction underpins a broad range of downstream tasks across many scientific domains. Recent advances and increasing adoption of black-box machine learning models for…

cs.LG2026

Kernel-based Optimally Weighted Conformal Time-Series Prediction

Jonghyeok Lee, Chen Xu, Yao Xie

In this work, we present a novel conformal prediction method for time-series, which we call Kernel-based Optimally Weighted Conformal Prediction Intervals (KOWCPI). Specifically, K…

stat.ML2025

Spatial Conformal Inference through Localized Quantile Regression

Hanyang Jiang, Yao Xie

Reliable uncertainty quantification at unobserved spatial locations, especially in the presence of complex and heterogeneous datasets, remains a core challenge in spatial statistic…