2024
TabDeco: A Comprehensive Contrastive Framework for Decoupled Representations in Tabular Data.
CoRR, 2024

CROPS: A Deployable Crop Management System Over All Possible State Availabilities.
CoRR, 2024

Deep Representation Learning for Multi-functional Degradation Modeling of Community-dwelling Aging Population.
CoRR, 2024

Residual-based Language Models are Free Boosters for Biomedical Imaging.
CoRR, 2024

Adaptive Ensembles of Fine-Tuned Transformers for LLM-Generated Text Detection.
Proceedings of the International Joint Conference on Neural Networks, 2024

The New Agronomists: Language Models are Experts in Crop Management.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Residual-based Language Models are Free Boosters for Biomedical Imaging Tasks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

SwitchTab: Switched Autoencoders Are Effective Tabular Learners.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
ReConTab: Regularized Contrastive Representation Learning for Tabular Data.
CoRR, 2023

2018
A data heterogeneity modeling and quantification approach for field pre-assessment of chloride-induced corrosion in aging infrastructures.
Reliab. Eng. Syst. Saf., 2018