Results 121 to 130 of about 110,849 (310)

Active Learning‐Accelerated Discovery of Fibrous Hydrogels with Tissue‐Mimetic Viscoelasticity

Advanced Functional Materials, EarlyView.
Active learning accelerates the design of fibrous hydrogels that mimic the viscoelasticity of native tissues. By integrating multi‐objective optimization and closed‐loop experimentation, this approach efficiently identifies optimal formulations from thousands of possibilities and decouples elasticity and viscosity. The resulting hydrogels offer tunable
Zhengkun Chen, Zheyuan Miao, Gary Tom, Austin H. Cheng, Elizaveta Gusarova, Benjamen Zondag, Tianyi Wu, Dianoosh Kalhori, Boris Hinz, Milad Abolhasani, Alán Aspuru‐Guzik, Eugenia Kumacheva   +11 more
wiley   +1 more source

Framework and Algorithms for Accelerating Training of Semi-supervised Graph Neural Network Based on Heuristic Coarsening Algorithms [PDF]

Jisuanji kexue
Graph neural network is the mainstream tool of graph machine learning at the current stage,and it has broad development prospects.By constructing an abstract graph structure,the graph neural network model can be used to efficiently deal with problems in ...
CHEN Yufeng , HUANG Zengfeng
doaj   +1 more source

Graph Neural Networks at a Fraction

12 pages, 2 figures, accepted at PAKDD ...
Rucha Bhalchandra Joshi, Sagar Prakash Barad, Nidhi Tiwari, Subhankar Mishra   +3 more
openaire   +2 more sources

Graph Neural Networks on Graph Databases

CoRR
Training graph neural networks on large datasets has long been a challenge. Traditional approaches include efficiently representing the whole graph in-memory, designing parameter efficient and sampling-based models, and graph partitioning in a distributed setup. Separately, graph databases with native graph storage and query engines have been developed,
Dmytro Lopushanskyy, Borun Shi
openaire   +2 more sources

Self‐Healing and Stretchable Synaptic Transistor

Advanced Functional Materials, EarlyView.
A self‐healing stretchable synaptic transistor (3S‐T) is realized using a p‐PVDF‐HFP‐DBP/PDMS‐MPU‐IU bilayer as gate insulator, where dipole‐dipole interaction enhances polarization to achieve a large memory window. Leveraging its neuronal biomimicry, the synaptic transistor demonstrates electrically compatibility with the biological brain. Furthermore,
Hyongsuk Choo, Sangyong Park, Yoonyi Jeong, Jaepyo Jang, Duhwan Seong, In Soo Kim, Myung‐Gil Kim, Mikyung Shin, Minah Suh, Donghee Son, Jin‐Hong Park   +10 more
wiley   +1 more source

Cascade2vec: Learning Dynamic Cascade Representation by Recurrent Graph Neural Networks

IEEE Access, 2019
An information dissemination network (i.e., a cascade) with a dynamic graph structure is formed when a novel idea or message spreads from person to person.
Zhenhua Huang, Zhenyu Wang, Rui Zhang
doaj   +1 more source

Rule-Guided Graph Neural Networks for Explainable Knowledge Graph Reasoning

The connections between symbolic rules and neural networks have been explored in various directions, including rule mining through neural networks and rule-based explanation for neural networks.
Wang, Zhe, Zhuang, Zhiqiang, Wang, Z, Ma, S, Ma, Suxue, Wang, Kewen, Wang, K, Zhuang, Z   +7 more
core   +1 more source

Computational Capabilities of Graph Neural Networks

, 2009
In this paper, we will consider the universal approximation properties of a recently introduced neural network model called graph neural network (GNN) which can be used to process structured data inputs, e.g.
HAGENBUCHNER M., TSOI A. C., SCARSELLI F., MONFARDINI G., GORI M.   +4 more
core   +1 more source

Texoskeletons: Developing the Fundamental Technologies for Creating Intelligent Soft Robotic Clothing With Integrated 1D Sensors and Actuators

Advanced Functional Materials, EarlyView.
ABSTRACT Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile‐based exoskeletons (Texoskeletons) built using 1D sensors and actuators.
Amy Lukomiak, Rameesh Bulathsinghala, Jack Varga, Shuxin Meng, Kalana Marasinghe, Imaad Refai, Biyon Fernando, Amitkumar Patel, Chamika M. Halloluwa‐Arachchige, Carlos Oliveira, Arash M. Shahidi, Zahra Rahemtulla, Alexander Turner, Ziyun Ding, Bernard X. W. Liew, Andy Kerr, Ezio Preatoni, Theo Hughes‐Riley, Ishara Dharmasena, Pasindu Lugoda   +19 more
wiley   +1 more source

Enhancing Anti-Money Laundering Frameworks: An Application of Graph Neural Networks in Cryptocurrency Transaction Classification

IEEE Access
Cryptocurrency money laundering is a pressing issue, as it not only facilitates and hides criminal activities but also disrupts markets and the overall financial system.
Stefano Ferretti, Gabriele D'Angelo, Vittorio Ghini   +2 more
doaj   +1 more source