1 citations · 4 across the 16 of their papers we have counts for
16 papers
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…
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…
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…
DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data
Al Zadid Sultan Bin Habib, Gianfranco Doretto, Donald A. Adjeroh
High-dimensional tabular data lacks a natural feature order, limiting the applicability of permutation-sensitive deep learning models. We propose DynaTab, a dynamic feature orderin…
SemLT3D: Semantic-Guided Expert Distillation for Camera-only Long-Tailed 3D Object Detection
Hao Vo, Khoa Vo, Thinh Phan +5
Camera-only 3D object detection has emerged as a cost-effective and scalable alternative to LiDAR for autonomous driving, yet existing methods primarily prioritize overall performa…
GUESS: Generative Uncertainty Ensemble for Self Supervision
Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh
Self-supervised learning (SSL) frameworks consist of pretext task, and loss function aiming to learn useful general features from unlabeled data. The basic idea of most SSL baselin…
Rethinking Self-Supervised Learning Within the Framework of Partial Information Decomposition
Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh
Self Supervised learning (SSL) has demonstrated its effectiveness in feature learning from unlabeled data. Regarding this success, there have been some arguments on the role that m…
Direct Coloring for Self-Supervised Enhanced Feature Decoupling
Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh
The success of self-supervised learning (SSL) has been the focus of multiple recent theoretical and empirical studies, including the role of data augmentation (in feature decouplin…
FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
Trong Thang Pham, Ngoc-Vuong Ho, Nhat-Tan Bui +8
Developing an interpretable system for generating reports in chest X-ray (CXR) analysis is becoming increasingly crucial in Computer-aided Diagnosis (CAD) systems, enabling radiolo…
Improving Accuracy and Generalization for Efficient Visual Tracking
Ram Zaveri, Shivang Patel, Yu Gu +1
Efficient visual trackers overfit to their training distributions and lack generalization abilities, resulting in them performing well on their respective in-distribution (ID) test…
TabSeq: A Framework for Deep Learning on Tabular Data via Sequential Ordering
Al Zadid Sultan Bin Habib, Kesheng Wang, Mary-Anne Hartley +2
Effective analysis of tabular data still poses a significant problem in deep learning, mainly because features in tabular datasets are often heterogeneous and have different levels…
Efficient Classification of Histopathology Images
Mohammad Iqbal Nouyed, Mary-Anne Hartley, Gianfranco Doretto +1
This work addresses how to efficiently classify challenging histopathology images, such as gigapixel whole-slide images for cancer diagnostics with image-level annotation. We use i…
Few-shot adaptation for morphology-independent cell instance segmentation
Ram J. Zaveri, Voke Brume, Gianfranco Doretto
Microscopy data collections are becoming larger and more frequent. Accurate and precise quantitative analysis tools like cell instance segmentation are necessary to benefit from th…
Current Topological and Machine Learning Applications for Bias Detection in Text
Colleen Farrelly, Yashbir Singh, Quincy A. Hathaway +7
Institutional bias can impact patient outcomes, educational attainment, and legal system navigation. Written records often reflect bias, and once bias is identified; it is possible…
ZEETAD: Adapting Pretrained Vision-Language Model for Zero-Shot End-to-End Temporal Action Detection
Thinh Phan, Khoa Vo, Duy Le +3
Temporal action detection (TAD) involves the localization and classification of action instances within untrimmed videos. While standard TAD follows fully supervised learning with…
Open-Fusion: Real-time Open-Vocabulary 3D Mapping and Queryable Scene Representation
Kashu Yamazaki, Taisei Hanyu, Khoa Vo +5
Precise 3D environmental mapping is pivotal in robotics. Existing methods often rely on predefined concepts during training or are time-intensive when generating semantic maps. Thi…