Results 71 to 80 of about 5,823,532 (214)
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 +12 more
wiley +1 more source
Graph Drawing Techniques for Geographic Visualization [PDF]
, 2004 Geovisualizers often need to represent data that consists of items related together. Such data sets can be abstracted to a mathematical structure, the graph.
Rodgers, Peter
core
Slanted Orthogonal Drawings: Model, Algorithms and Evaluations
, 2014 We introduce a new model in the context of non-planar orthogonal graph drawing that we call slanted orthogonal graph drawing. While in traditional orthogonal drawings each edge is made of alternating axis-aligned line segments, in slanted orthogonal ...
ROSELLI, VINCENZO +5 more
core +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 +5 more
wiley +1 more source
Representing Space: A Hybrid Genetic Algorithm for Aesthetic Graph Layout [PDF]
, 1998 This paper describes a hybrid Genetic Algorithm (GA) that is used to improve the layout of a graph according to a number of aesthetic criteria.
Rodgers, Peter, Hobbs, M.H.W.
core
Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
Advanced Science, EarlyView.This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning +3 more
wiley +1 more source
Dual‐Module Near‐Infrared Fluorophores Discovery System via Knowledge Transfer
Advanced Science, EarlyView.This study presents a dual‐module deep learning system for the design of near‐infrared (NIR) fluorophores. A large molecular library is generated and analyzed, leading to the suggestions of promising candidates. The effectiveness of the system is further validated through the synthesis, characterization, and in vivo imaging, demonstrating its potential
Yixin Zhu +7 more
wiley +1 more source
Graph-based discovery of ontology change patterns [PDF]
, 2011 Ontologies can support a variety of purposes, ranging from capturing conceptual knowledge to the organisation of digital content and information. However, information systems are always subject to change and ontology change management can pose challenges.
Abgaz, Yalemisew +2 more
core +2 more sources
Advanced Science, EarlyView.Based on the largest printable mesoscopic perovskite solar cells database we established, stacking model achieved precise PCE prediction (R2 = 0.73, MAE = 2.18%). Multiple experiments verified the accuracy of the model, which guided the fabrication of high‐PCE devices with an efficiency of 19.36%.
Hao Meng +9 more
wiley +1 more source
Molecular and Cellular Hallmarks of Age‐Related Vestibular Hair Cell Degeneration
Advanced Science, EarlyView.This study utilizes single‐cell RNA‐seq transcriptomes, advanced imaging, and electrophysiology to examine universal and cell‐type‐specific aging signatures of vestibular hair cells. The study shows that impaired hair bundle function is a key driver of age‐related vestibular dysfunction.
Samadhi Kulasooriya +10 more
wiley +1 more source