2 citations · 3 across the 7 of their papers we have counts for
7 papers
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…
Graph-Based Prediction Models for Data Debiasing
Dongze Wu, Hanyang Jiang, Yao Xie
Bias in data collection, arising from both under-reporting and over-reporting, poses significant challenges in critical applications such as healthcare and public safety. In this w…
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…
Spatio-Temporal Conformal Prediction for Power Outage Data
Hanyang Jiang, Yao Xie, Feng Qiu
In recent years, increasingly unpredictable and severe global weather patterns have frequently caused long-lasting power outages. Building resilience, the ability to withstand, ada…
Learning Cellular Network Connection Quality with Conformal
Hanyang Jiang, Elizabeth Belding, Ellen Zegure +1
In this paper, we address the problem of uncertainty quantification for cellular network speed. It is a well-known fact that the actual internet speed experienced by a mobile phone…
Conformal prediction for multi-dimensional time series by ellipsoidal sets
Chen Xu, Hanyang Jiang, Yao Xie
Conformal prediction (CP) has been a popular method for uncertainty quantification because it is distribution-free, model-agnostic, and theoretically sound. For forecasting problem…
Mobile Internet Quality Estimation using Self-Tuning Kernel Regression
Hanyang Jiang, Henry Shaowu Yuchi, Elizabeth Belding +2
Modeling and estimation for spatial data are ubiquitous in real life, frequently appearing in weather forecasting, pollution detection, and agriculture. Spatial data analysis often…