2 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
LoopExpose: An Unsupervised Framework for Arbitrary-Length Exposure Correction
Ao Li, Chen Chen, Zhenyu Wang +3
Exposure correction is essential for enhancing image quality under challenging lighting conditions. While supervised learning has achieved significant progress in this area, it rel…
SimMLM: A Simple Framework for Multi-modal Learning with Missing Modality
Sijie Li, Chen Chen, Jungong Han
In this paper, we propose SimMLM, a simple yet powerful framework for multimodal learning with missing modalities. Unlike existing approaches that rely on sophisticated network arc…
Missing-Modality-Aware Graph Neural Network for Cancer Classification
Sina Tabakhi, Chen, Haiping Lu
A key challenge in learning from multimodal biological data is missing modalities, where data from one or more modalities are absent for some patients. Existing approaches either e…
Multimodal Latent Fusion of ECG Leads for Early Assessment of Pulmonary Hypertension
Mohammod N. I. Suvon, Shuo Zhou, Prasun C. Tripathi +7
Recent advancements in early assessment of pulmonary hypertension (PH) primarily focus on applying machine learning methods to centralized diagnostic modalities, such as 12-lead el…
Foundation-Model-Boosted Multimodal Learning for fMRI-based Neuropathic Pain Drug Response Prediction
Wenrui Fan, L. M. Riza Rizky, Jiayang Zhang +5
Neuropathic pain, affecting up to 10% of adults, remains difficult to treat due to limited therapeutic efficacy and tolerability. Although resting-state functional MRI (rs-fMRI) is…