5 papers · 1 filter
Logit-Coordinate Generative Models for Mixed Continuous-Categorical Tabular Data
Yuefei Shen, Xiaotong Shen
Mixed continuous--categorical data pose a representation problem for continuous generative models. Flow Matching and Gaussian diffusion operate in Euclidean spaces, whereas categor…
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
High-dimensional generative modeling is fundamentally a manifold-learning problem: real data concentrate near a low-dimensional structure embedded in the ambient space. Effective g…
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…
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…