Jianqing Fan

UTOPIA: Universally Trainable Optimal Prediction Intervals Aggregation

2023 · arXiv (Cornell University)

Uncertainty quantification in prediction presents a compelling challenge with vast applications across various domains, including biomedical science, economics, and weather forecasting. There exists a wide array of methods for constructing prediction intervals, such as quantile …

Robust Transfer Learning with Unreliable Source Data

2023 · arXiv (Cornell University)

This paper addresses challenges in robust transfer learning stemming from ambiguity in Bayes classifiers and weak transferable signals between the target and source distribution. We introduce a novel quantity called the ''ambiguity level'' that measures …

Opportunities and challenges of diffusion models for generative AI

2024 · National Science Review

Diffusion models, a powerful and universal generative artificial intelligence technology, have achieved tremendous success and opened up new possibilities in diverse applications. In these applications, diffusion models provide flexible high-dimensional data modeling, and act as …