Results 101 to 110 of about 4,069,375 (260)
Learning meshless parameterization with graph convolutional neural networks
, 2023 International audienceThis paper proposes a deep learning approach for parameterizing an unorganized or scattered point cloud in R 3 with graph convolutional neural networks.
Giannelli, Carlotta +3 more
core +1 more source
Robust Stitching Interface and Deep Learning Empowered Hydrogel Human‐Machine Interface
Advanced Science, EarlyView.A molecular design strategy is presented that exploits synergistic carboxylate anion–quaternary ammonium interactions to simultaneously strengthen the hydrogel–PET interface and the bulk hydrogel network. Integrated with deep learning signal processing, the stable hydrogel–PET interface enables consistent signal acquisition and reliable human‐machine ...
Hao Dong +11 more
wiley +1 more source
Neuromorphic Devices and Computing for Sensing, Memory, and Control
Advanced Science, EarlyView.This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu +2 more
wiley +1 more source
Review of blockchain application with Graph Neural Networks, Graph Convolutional Networks and Convolutional Neural Networks [PDF]
This paper reviews the applications of Graph Neural Networks (GNNs), Graph Convolutional Networks (GCNs), and Convolutional Neural Networks (CNNs) in blockchain technology.
Liason, Claudia, Ancelotti, Amy
core +1 more source
A Relationship-Aware Feature Update Method for Enhanced Graph-Based Neural Networks
IEEE AccessThis paper presents a novel feature update method that leverages the relationships among batch elements, addressing scenarios both with and without an external graph.
Conggui Huang
doaj +1 more source
Advanced Science, EarlyView.Single‐cell, spatial, molecular, and pathology analyses identify a CDH3‐associated malignant epithelial state in thymic epithelial tumors. This state links stem‐like and EMT programs to M2 macrophage–rich immunosuppressive niches, genomic instability, poor survival, and drug vulnerability.
Yuntao Feng +13 more
wiley +1 more source
Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes
Advanced Science, EarlyView.StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley +1 more source
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 +6 more
wiley +1 more source
Journal of Big DataLarge-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 +2 more
doaj +1 more source
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 +9 more
wiley +1 more source