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.
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Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
ReConTab: Regularized Contrastive Representation Learning for Tabular Data.
CoRR, 2023
A data heterogeneity modeling and quantification approach for field pre-assessment of chloride-induced corrosion in aging infrastructures.
Reliab. Eng. Syst. Saf., 2018