Author

Tie-Ming Liu

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Preprint Sep 2026

RiVaT-Fuse: Reliability-Calibrated Variational Tensor Fusion with Matrix-Valued Trust for Multimodal Prediction under Modality Uncertainty

Multimodal prediction from images and structured metadata requires integrating complementary evidence whose reliability can vary across samples and latent directions. A single confidence weight per modality cannot capture this directional variation. We propose RiVaT-Fuse, a reliability-calibrated variational tensor fus...

Yin Xu, Tie-Ming Liu, Ye Liang · 2 citations

#machine learning Preprint Sep 2026

RiVaT-Fuse: Reliability-Calibrated Variational Tensor Fusion for Multimodal Prediction under Modality Uncertainty

RiVaT-Fuse is proposed, a reliability-calibrated variational tensor fusion framework that defines fusion as sample-wise latent-state estimation and achieves the strongest overall predictive rank among direct representation-level baselines while improving probability and label stability under perturbation.

Yin Xu, Tie-Ming Liu, Ye Liang et al. · 1 citation

#machine learning Preprint Sep 2026

DR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction

DR-LabStack is designed and implemented, a React-Flask web system integrating four externally developed pretrained models: RuleFit, Pruned RuleFit, Elaborative XGBoost, and Two-level Ensemble, a reusable interaction and serving workflow for heterogeneous DR models.

Ying-Fan Xu, Tie-Ming Liu, Ye Liang · 0 citations