Optimized Nanoparticle Structures

Figshare2024-12-05 更新2026-04-28 收录

纳米材料设计

图神经网络

数据链接：

https://figshare.com/articles/dataset/Optimized_Nanoparticle_Structures/27973206 数据链接链接失效反馈

官方服务：

资源简介：

Optimized nanoparticle structures discovered by optimizing augmented Hetero-GNN model

创建时间：

2024-12-05

StructureSAT

图神经网络

SAT布尔可满足性问题

StructureSAT是一个大规模的饱和问题（SAT）数据集，由新南威尔士大学计算机科学与工程学院创建。该数据集包含来自不同问题领域的多样化SAT问题，旨在研究图神经网络（GNN）在SAT问题上的泛化能力。数据集涵盖了随机、设计、伪工业和工业等11个SAT领域，并研究了9种对传统SAT求解器有影响的图形结构属性。数据集通过结构属性对问题领域进行细分，以研究不同结构属性对GNN求解器泛化能力的影响

arXiv2025-02-17 更新110

Versatile Macroscale Concentration Gradients of Nanoparticles in Soft Nanocomposites

纳米材料设计

纳米颗粒浓度梯度控制

Nanocomposite materials benefit from the diverse physicochemical properties featured by nanoparticles, and the presence of nanoparticle concentration gradients can lend functions to macroscopic materi

NIAID Data Ecosystem50

RF-GCN_Dataset

图神经网络

图结构

Cora, Citeseer, and Pubmed are three citation networks for research papers, where nodes represent publications and edges denote citation links. Node attributes consist of bag-of-words representat

IEEE50

Codes and datasets for AAAI 2021 paper "Learning to Pre-train Graph Neural Networks"

图神经网络

训练

This record contains the dataset and codes to reproduce the published paper. Please refer to the live GitHub repository (https://github.com/rootlu/L2P-GNN) for more information. A copy of the GitHub r

DataCite Commons2022-10-25 更新100

GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts

几何深度学习基准

图神经网络

The following contains the datasets described in the paper: GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts, and the associated code can be found at https://github.com/Graph-

Zenodo2023-11-06 更新50

Optimized Nanoparticle Structures

资源简介：

相关数据集