Learning Generalized Hybrid Proximity Representation for Image Recognition. - Zhiyuan Li 011; Anca L. Ralescu (ICTAI, 2022)

Interpretability of Neural Network With Physiological Mechanisms. - Anna Zou; Zhiyuan Li 011 (CoRR, 2022)

A novel Ontology-guided Attribute Partitioning ensemble learning model for early prediction of cognitive deficits using quantitative Structural MRI in very preterm infants. - Zhiyuan Li 011; Hailong Li; Adebayo Braimah; Jonathan R. Dillman; Nehal A. Parikh; Lili He 003 (NeuroImage, 2022)

Learning Empirical Bregman Divergence for Uncertain Distance Representation. - Zhiyuan Li 011; Ziru Liu; Anna Zou; Anca L. Ralescu (FUSION, 2023)

Generalized self-supervised contrastive learning with bregman divergence for image recognition. - Zhiyuan Li 011; Anca L. Ralescu (Pattern Recognit. Lett., 2023)

A novel collaborative self-supervised learning method for radiomic data. - Zhiyuan Li 011; Hailong Li; Anca L. Ralescu; Jonathan R. Dillman; Nehal A. Parikh; Lili He 003 (NeuroImage, 2023)

Joint self-supervised and supervised contrastive learning for multimodal MRI data: Towards predicting abnormal neurodevelopment. - Zhiyuan Li 011; Hailong Li; Anca L. Ralescu; Jonathan R. Dillman; Mekibib Altaye; Kim M. Cecil; Nehal A. Parikh; Lili He 003 (Artif. Intell. Medicine, 2024)

Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome. - Hailong Li; Junqi Wang 001; Zhiyuan Li 011; Kim M. Cecil; Mekibib Altaye; Jonathan R. Dillman; Nehal A. Parikh; Lili He 003 (NeuroImage, 2024)