collaborators

5 papers

cs.CV2026

iStructTab: Structured Feature Sequencing for Multimodal Learning of Image and Tabular Data

Al Zadid Sultan Bin Habib, Md Younus Ahamed, Prashnna Gyawali +2

Multimodal learning of images and tabular data is often impaired by ineffective representations, resulting in redundancy, dispersion, and generalization problems. To tackle this ch…

cs.CV2026

Pediatric Bone Age Prediction Using Deep Learning

Al Zadid Sultan Bin Habib, Md. Ekramul Islam, Md Asif Bin Syed +2

Pediatric bone age prediction is a crucial task in clinical practice that can help diagnose endocrine disorders and provide insight into a child's growth and development. However,…

cs.LG2026

AquaAugmentor: A Novel Feature Augmentation Algorithm for Water Potability Prediction

Muntasir Tabasum, Al Zadid Sultan Bin Habib, Tanpia Tasnim +3

Access to potable water is crucial for health, economic development, and sustainability. However, accurately classifying water quality remains a significant challenge due to the co…

cs.LG2026

BSTabDiff: Block-Subunit Diffusion Priors for High-Dimensional Tabular Data Generation

Al Zadid Sultan Bin Habib, Md Younus Ahamed, Prashnna Gyawali +2

High-Dimensional Low-Sample Size (HDLSS) tabular domains (e.g., omics) are characterized by , where = number of samples, and = number of features. Such domains oft…

cs.LG2026

GOTabPFN: From Feature Ordering to Compact Tokenization for Tabular Foundation Models on High-Dimensional Data

Al Zadid Sultan Bin Habib, Md Younus Ahamed, Prashnna Kumar Gyawali +2

We investigate how to make small tabular foundation models effective for High-Dimensional, Low-Sample Size (HDLSS) tabular prediction without retraining large backbones. We introdu…