4 papers · 1 filter
Generative Score Inference for Multimodal Data
Xinyu Tian, Xiaotong Shen
Accurate uncertainty quantification is crucial for making reliable decisions in various supervised learning scenarios, particularly when dealing with complex, multimodal data such…
Manifold-Aligned Generative Transport
Xinyu Tian, Xiaotong Shen
Many high-dimensional datasets concentrate near a low-dimensional structure embedded in the ambient space. Generative models for such data must control off-support mass while remai…
Generative Distribution Prediction: A Unified Approach to Multimodal Learning
Xinyu Tian, Xiaotong Shen
Accurate prediction with multimodal data-encompassing tabular, textual, and visual inputs or outputs-is fundamental to advancing analytics in diverse application domains. Tradition…
Enhancing Accuracy in Generative Models via Knowledge Transfer
Xinyu Tian, Xiaotong Shen
This paper investigates the accuracy of generative models and the impact of knowledge transfer on their generation precision. Specifically, we examine a generative model for a targ…