Results 81 to 90 of about 36,148 (258)

Intelligent Smart Grid Energy Management for EV Charging Stations Using GOA–HMGIGCN

Algorithms
Electric Vehicle Charging Stations (EVCSs) have become increasingly important due to the growing penetration of electric vehicles (EVs) and renewable-based power generation.
Mlungisi Ntombela
doaj   +1 more source

Source Localization of Network Information Propagation via Invertible Graph Diffusion [PDF]

Jisuanji kexue yu tansuo
With the development of society, security issues in various types of networks have become increasingly prominent, especially network propagation issues.
ZHAI Wenshuo, ZHAO Xiang, CHEN Dong
doaj   +1 more source

Motif-based Convolutional Neural Network on Graphs

CoRR, 2017
This paper introduces a generalization of Convolutional Neural Networks (CNNs) to graphs with irregular linkage structures, especially heterogeneous graphs with typed nodes and schemas. We propose a novel spatial convolution operation to model the key properties of local connectivity and translation invariance, using high-order connection patterns or ...
Aravind Sankar, Xinyang Zhang 0002, Kevin Chen-Chuan Chang   +2 more
openaire   +2 more sources

Functional Mapping of Neurodevelopmental Disease Pathways to Key Neurodevelopmental Processes Represented in the Developmental Neurotoxicity In Vitro Testing Battery

Advanced Science, EarlyView.
Human‐relevant methods are essential for modern chemical safety assessment. This study helps define the capabilities and boundaries of an in vitro testing battery for developmental neurotoxicity by exploring its biological applicability domain. By linking neurodevelopmental disease‐related pathways to key neurodevelopmental processes, the work enhances
Eliska Kuchovska, Kristina Bartmann, Georgea Raad, Mats Schade, Luiz Ladeira, Arif Dönmez, Jördis Klose, Nicolai Görts, Denis Polozij, Lynn‐Christin Saborowski, Farina Bendt, Bernard Staumont, Liesbet Geris, Katharina Koch, Ellen Fritsche   +14 more
wiley   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES

Advanced Science, EarlyView.
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu, Wanpeng Zou, Yuekai Li, Jiayi Wang, Mingxuan Cai, Hongmin Cai   +5 more
wiley   +1 more source

Sessionbased graph convolutional recurrent neural networks recommendation model

四川大学学报. 自然科学版, 2021
The session based recommendation is a subtask of recommendation system, which addresses the recommendation problem about anonymous users. Although the existing methods with the graph neural network for recommendation have achieved good results, which are
CAO Wan-Ping, ZHOU Gang, CHEN Li, CUI Lan-Lan   +3 more
doaj  

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source