Results 131 to 140 of about 3,278,052 (298)

Graph Convolutional Networks for Text Classification

, 2019
Text classification is an important and classical problem in natural language processing. There have been a number of studies that applied convolutional neural networks (convolution on regular grid, e.g., sequence) to classification.
Luo, Yuan, Yao, Liang, Mao, Chengsheng
core   +1 more source

A Site‐Aware Representation Learning Framework For Unified Molecular Interaction Modeling and Generative Design

Advanced Science, EarlyView.
MolDBG is a site‐aware, sequence‐only framework that unifies drug‐target affinity prediction, binding‐site identification, and affinity‐conditioned molecular generation for structured proteins. Guided by multi‐task binding‐site supervision, it aligns interaction‐critical residues before learning drug‐target representations and simultaneously infers ...
Gang Luo, Qianqian Zhang, Chenhao Wang, Zhiheng Yi, Alex Jinpeng Wang, Jing Tang, Min Li   +6 more
wiley   +1 more source

Difference-attention graph convolutional network for skeleton-based gesture recognition

Journal of King Saud University: Computer and Information Sciences
Graph Convolutional Networks (GCNs) have been widely applied to skeleton-based gesture recognition tasks and have achieved remarkable performance. The currently proposed dynamic and topology-non-shared graph convolutional networks outperform conventional
Yadong Wang, Mingxin Yu, Ning Li, Eryang Gao, Guofang Wang, Lianqing Zhu   +5 more
doaj   +1 more source

Variational Graph Convolutional Networks for Dynamic Graph Representation Learning

IEEE Access
The ubiquitous and ever-evolving nature of cyber threats demands innovative approaches that can adapt to the dynamic relationships and structures within network data.
Aabid A. Mir, Megat F. Zuhairi, Shahrulniza Musa, Meshari H. Alanazi, Abdallah Namoun   +4 more
doaj   +1 more source

Tensor Graph Convolutional Networks for Text Classification

, 2020
Compared to sequential learning models, graph-based neural networks exhibit some excellent properties, such as ability capturing global information. In this paper, we investigate graph-based neural networks for text classification problem.
Zhang, Xiao, Liu, Xien, You, Xinxin, Lv, Ping, Wu, Ji   +4 more
core   +1 more source

STWave: Fine‐Scale Spatial Structure Discovery in Microscopic‐Resolution Spatial Transcriptomics via Patchwise Wavelet Graphs

Advanced Science, EarlyView.
STWave transforms massive microscopic‐resolution spatial transcriptomics into interpretable fine‐scale tissue maps through patch‐wise inference, wavelet‐based multi‐scale encoding, and dual‐domain reconstruction. It reduces noise while preserving weak spatial signals, enabling efficient analysis of 6 40 000 spots of 2.47 GB GPU memory and revealing ...
Tao Jiang, Songming Zhang, Xiaofeng Chen, Xiongtao Xiao, Wenming Cao, Weikai Li, Tong Zhao, Bing Li, Xinyue Xu, Zhongshan Li   +9 more
wiley   +1 more source

A Unified Hierarchical Multiscale Fusion Framework for Drug–Target Affinity Prediction: From Benchmark Performance to Nanomolar Inhibitor Discovery

Advanced Science, EarlyView.
A multimodal fusion framework integrating sequence, atomic, and fragment representations captures drug–target interactions across multiple scales. The model delivers strong predictive performance and enables efficient virtual screening. Applied to hematopoietic progenitor kinase 1 (HPK1), it identifies structurally diverse inhibitors with nanomolar ...
Shuo Liu, Xiang Zhang, Haixia Feng, Yuquan Li, Xiaoqing Gong, Yong Liang, Xiaojun Yao, Huanxiang Liu   +7 more
wiley   +1 more source

Advancing Link Prediction with a Hybrid Graph Neural Network Approach

Mathematics
Social media platforms produce extensive user–item interaction data that demand advanced analytical models for effective personalization. This study investigates the link prediction task within social recommendation systems using Graph Neural Networks ...
Siwar Gharsallah, Samah Yahia, Wided Bouchelligua, Tahani Bouchrika   +3 more
doaj   +1 more source

AI‐Assisted Tumor Boundary Delineation via Targeted Ultrasmall Iron Oxide Nanoprobe for High‐Contrast HER2‐Positive Tumor Imaging

Advanced Science, EarlyView.
A novel targeted and pH‐responsive MRI contrast agent was integrated with a 3D nnU‐Net deep learning framework to enable accurate delineation of tumor boundary morphology in HER2‐positive breast cancer imaging. ABSTRACT Breast cancer continues to be a leading cause of cancer‐related mortality in women globally, where precise diagnosis and clear tumor ...
Jiaying Zheng, Yi Zhu, Xinrui Li, Sunxian Dai, Xiangyuan Ma, Hongwei Lu, Zhongling Wang, Benqing Zhou   +7 more
wiley   +1 more source

Inverse link prediction with graph convolutional networks for knowledge-preserving sparsification in cheminformatics

Journal of Big Data
Large-scale cheminformatics datasets, such as those used in drug discovery and materials science, are often represented as dense similarity graphs; however, their complexity hinders scalable analysis and interpretability.
Elnaz Bangian Tabrizi, Mehrdad Jalali, Mahboobeh Houshmand   +2 more
doaj   +1 more source