5 papers
From Synthetic Priors to Model Behavior: Structural Coverage in Tabular Foundation Models
He Zhao, Ryan Thompson, Daniel M. Steinberg +3
Tabular foundation models (TFMs) are commonly pretrained on large collections of procedurally generated synthetic tasks, yet it remains unclear how well these synthetic pretraining…
Ordering-based Causal Discovery via Generalized Score Matching
Vy Vo, He Zhao, Trung Le +2
Learning DAG structures from purely observational data remains a long-standing challenge across scientific domains. An emerging line of research leverages the score of the data dis…
Optimal Transport for Structure Learning Under Missing Data
Vy Vo, He Zhao, Trung Le +2
Causal discovery in the presence of missing data introduces a chicken-and-egg dilemma. While the goal is to recover the true causal structure, robust imputation requires considerin…
A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation
Tuan Nguyen, Van Nguyen, Trung Le +3
Unsupervised domain adaptation (UDA) aims to transfer knowledge from a labeled source domain to an unlabeled target domain. In this paper, we introduce a novel approach called clas…
Cross-adversarial local distribution regularization for semi-supervised medical image segmentation
Thanh Nguyen-Duc, Trung Le, Roland Bammer +3
Medical semi-supervised segmentation is a technique where a model is trained to segment objects of interest in medical images with limited annotated data. Existing semi-supervised…