Results 121 to 130 of about 4,082,283 (306)

Biodegradable and Biocompatible Functional Polymers for Biomedical Applications

Advanced Functional Materials, EarlyView.
Biodegradable and biocompatible functional polymers integrate electrical, mechanical, and stimuli‐responsive functionalities while enabling programmed degradation under physiological conditions. This review introduces recent advances in conductive, shape‐memory, self‐healing, photocurable, and adhesive polymer systems, emphasizing material design ...
Won Bae Han, Shuvra Mondal, Sungkeun Han, Chan‐Hwi Eom, Venkata Ramesh Naganaboina, Suk‐Won Hwang   +5 more
wiley   +1 more source

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

Entity alignment via graph neural networks: a component-level study

, 2023
Entity alignment plays an essential role in the integration of knowledge graphs (KGs) as it seeks to identify entities that refer to the same real-world objects across different KGs.
Shu, Yanfeng, Zhang, Ji, Chi, Chi-Hung, Huang, Guangyan, He, Jing   +4 more
core   +1 more source

Multimode Oxide‐Based Optoelectronic Memtransistor for In‐Sensor Vision Processing

Advanced Functional Materials, EarlyView.
A multimode optoelectronic memtransistor (OEMT) is demonstrated for vision explainable artificial intelligence (VXAI) hardware. By integrating optical sensing, electrical masking, and non‐volatile memory, the device enables key operations required for generating saliency information.
Min Gu Lee, Geunyoung Kim, Hwa Young Kim, Do Hoon Kim, Hanchan Song, Huisu Noh, Jungwan Noh, Seungwoo Lee, Sang‐Hee Ko Park, Himchan Cho, Kyung Min Kim   +10 more
wiley   +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

Convolutional Graph Neural Networks

2019 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
Convolutional neural networks (CNNs) restrict the, otherwise arbitrary, linear operation of neural networks to be a convolution with a bank of learned filters. This makes them suitable for learning tasks based on data that exhibit the regular structure of time signals and images.
Fernando Gama, Antonio G. Marques, Geert Leus, Alejandro Ribeiro   +3 more
openaire   +4 more sources

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

Integrating convolutional neural networks into a sparse distributed representation model based on mammalian cortical learning

, 2016
Biological brains exhibit a remarkable capacity to recognise real-world patterns effectively. Despite major advances in neuroscience over the last few decades, an understanding of the brain's underlying mechanisms for pattern recognition remains ...
Daniel E. Padilla, McDonnell, M.D., Mark D. McDonnell, Padilla, D.E.   +3 more
core   +1 more source

Predicting flux in Discrete Fracture Networks via Graph Informed Neural Networks [PDF]

, 2021
Discrete Fracture Network (DFN) flow simulations are commonly used to determine the outflow in fractured media for critical applications. Here, we extend the formulation of spatial graph neural networks with a new architecture, called Graph-Informed ...
Pieraccini, Sandra, Berrone, Stefano, Vaccarino, Francesco, Della Santa, Francesco, Mastropietro, Antonio   +4 more
core  

Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing

Advanced Functional Materials, EarlyView.
A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin, Eunjoo Yoo, Ki‐Hoon Son, Hyun‐Sik Kim, Dae‐Hee Han, Jeong Hyeon Son, Seung Hwan Lee, Hong‐Sub Lee   +7 more
wiley   +1 more source