1 citations · 1 across the 7 of their papers we have counts for
8 papers
Statistical Gains from Looped Estimation under Parameter Budgets
Xinyu Tian, Xiaotong Shen
Memory constraints in artificial intelligence motivate accurate function approximation with fewer parameters. We study looping, which repeatedly composes one update function with s…
Region-Graph Optimal Transport Routing for Mixture-of-Experts Whole-Slide Image Classification
Xin Tian, Jiuliu Lu, Ephraim Tsalik +3
Multiple Instance Learning (MIL) is the dominant framework for gigapixel whole-slide image (WSI) classification in computational pathology. However, current MIL aggregators route a…
A Utility-preserving De-identification Pipeline for Cross-hospital Radiology Data Sharing
Chenhao Liu, Zelin Wen, Yan Tong +7
Large-scale radiology data are critical for developing robust medical AI systems. However, sharing such data across hospitals remains heavily constrained by privacy concerns. Exist…
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…
Conditional Data Synthesis Augmentation
Xinyu Tian, Xiaotong Shen
Reliable machine learning and statistical analysis rely on diverse, well-distributed training data. However, real-world datasets are often limited in size and exhibit underrepresen…
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…